Informacije

Kako naučiti biomatematiku?

Kako naučiti biomatematiku?


We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

Trenutno sam student matematike i istražujući na internetu otkrivam da postoji oblast koja se zove "biomatematika". Izgleda tako zanimljivo. Koriste teoriju grafova i topologiju za opisivanje ćelija i strukture DNK. Bila je to ljubav na prvi pogled, jer jako volim matematiku i biologiju.

Čitam knjigu "Clinically Oriented Anatomy" Keitha L. Moorea i "Essential Cells Biology" Brucea Albertsa, ali ne znam radim li dobro. Ako neko zna kako početi učiti ovu nauku, bio bih mu jako zahvalan.


MathsBio je prilično veliko polje. To je interdisciplinarna grana koja je korisna u mnogim granama u biologiji kao što su biofizika, biomedicina, genetika i molekularna biologija. Primijenjena matematika se općenito koristi za modeliranje i razumijevanje bioloških pojava gdje se moramo baviti velikom količinom podataka, na primjer upotrebom teorije grafova za analizu biokemijskih mreža. Sistemska biologija je novo područje koje koristi mnogo matematike.

Knjigu biste trebali odabrati ovisno o području u kojem želite koristiti matematiku, iako je potrebno poznavanje elementarne biologije. Predlažem neke knjige koje pokrivaju široku primjenu matematike u biologiji.

Matematička biologija: I. Uvod JD Murray

Za sistemsku biologiju:

Matematičko modeliranje u sistemskoj biologiji: Uvod Brian Ingalls


Stvarno mi se sviđa "Vodič za biologe za matematičko modeliranje u ekologiji i evoluciji" Sarah P. Otto i Troy Day, iako je specifičniji za biologiju i evoluciju - što je možda bilo prvo polje u biologiji u kojem se koristi matematika.


Odsjek za matematiku

Sa brzim rastom u polju biologije širom svijeta, paralelno se stavlja naglasak na kvantifikaciju u biologiji. Ovo pruža brojne mogućnosti pojedincima obučenim u kvantitativnim disciplinama, kao što je matematika, uz dodatnu obuku o temama koje su ključne za rješavanje bioloških problema.

Diplomski program Biomatematika (ili Matematička biologija) ima za cilj pružiti studentima ovu široku obuku. Pridruženi fakulteti imaju širok spektar stručnosti, uključujući biološko modeliranje i nauku o podacima. Ove teme su obrađene u fleksibilnom kursu, koji omogućava naglasak na modeliranju ili nauci o podacima. Doktorski program nudi studentima mogućnost provođenja istraživanja sa fakultetima o širokom rasponu bioloških tema, au nekim slučajevima uključuje interakciju s eksperimentalnim laboratorijima na FSU -u ili drugdje. Program je bio vrlo uspješan u postavljanju diplomaca na dobre postdoktorske i fakultetske pozicije u i izvan SAD -a

&kopiraj Državni univerzitet Floride
Tallahassee, FL 32306

208 Love Building, 1017 Academic Way
Tallahassee, FL 32306-4510
Telefon: 850-644-2202 Fax: 850-644-4053


Top 10 najpopularnijih Ostali fakulteti za biomatematiku i bioinformatiku

Yale University

New Haven, Connecticut

Ponuđene fakultetske diplome: Diplomirali, magistrirali

  • Biohemija/Biofizika i molekularna biologija
  • Biologija/Biološke nauke
  • Ćelijska/ćelijska i molekularna biologija
  • Ćelijska/ćelijska biologija i histologija
  • Evoluciona biologija
  • Genetika
  • Imunologija
  • Medicinska mikrobiologija i bakteriologija
  • Neurobiologija i anatomija

Univerzitet u južnoj Kaliforniji

Los Angeles, California

Nude se fakultetske diplome: Program sertifikata, diplome saradnika, diplome, master

  • Biohemija
  • Biokemija/Biofizika i molekularna biologija
  • Biologija/Biološke nauke
  • Biophysics
  • Biostatistika
  • Biologija mora i biološka oceanografija
  • Mikrobiologija i imunologija
  • Ostala biokemija, biofizika i molekularna biologija
  • Ostala biomatematika i bioinformatika

Koledž Harvey Mudd

Claremont, Kalifornija

Nude se fakultetske diplome: Bachelors Degree

  • Biologija/Biološke nauke
  • Ostala biokemija, biofizika i molekularna biologija
  • Ostala biomatematika i bioinformatika

Washington State University, Pullman

Pullman, Washington

Ponuđene fakultetske diplome: Program sertifikata, diplome saradnika, diplome, master

  • Animal Genetics
  • Biohemija
  • Biokemija/Biofizika i molekularna biologija
  • Biologija/Biološke nauke
  • Biotehnologija
  • Botanika/Biologija biljaka
  • Entomology
  • Vježba fiziologija
  • Opća zoologija/Biologija životinja

Lambuth University

Memphis, Tennessee

Nude se fakultetske diplome: Bachelors Degree

Univerzitet u Memphisu

Memphis, Tennessee

Ponuđene fakultetske diplome: Diplomirali, magistrirali

Institut za tehnologiju Floride

Melbourne, Florida

Nude se fakultetske diplome: Saradnici, diplome, magistri

  • Biologija vode/Limnologija
  • Biohemija
  • Biologija/Biološke nauke
  • Biomedicinske nauke
  • Biotehnologija
  • Ćelijska/ćelijska i molekularna biologija
  • Conservation Biology
  • Ekologija
  • Biologija mora i biološka oceanografija

Univerzitet Indiana, Bloomington

Bloomington, Indijana

Ponuđene fakultetske diplome: Program sertifikata, diplome saradnika, diplome, master

  • Biohemija
  • Bioinformatika
  • Biologija/Biološke nauke
  • Biostatistics
  • Biotehnologija
  • Opća zoologija/Biologija životinja
  • Mikrobiologija
  • Druge biološke i biomedicinske nauke
  • Ostala biomatematika i bioinformatika

Univerzitet u Kaliforniji, Los Angeles

Los Angeles, California

Nude se fakultetske diplome: Diplomirali, magistrirali

  • Biohemija
  • Bioinformatika
  • Biologija/Biološke nauke
  • Biophysics
  • Biostatistics
  • Ćelija/ćelijska i molekularna biologija
  • Ekologija
  • Epidemiologija
  • Biologija mora i biološka oceanografija

Univerzitet St Thomas, Houston

Hjuston, Teksas

Ponuđene fakultetske diplome: Program certifikata, prvostupnici, magistri

  • Biohemija
  • Biologija/Biološke nauke
  • Ostala biomatematika i bioinformatika

Washington University u St Louisu

Saint Louis, Missouri

Ponuđene fakultetske diplome: Program certifikata, diplome saradnika, diplome, magistri

  • Biologija/Biološke nauke
  • Biomedicinske nauke
  • Ekologija
  • Biologija okoliša
  • Epidemiologija
  • Ostala biohemija, biofizika i molekularna biologija
  • Ostala biomatematika i bioinformatika

Šta je ovo?

Kako bismo vam pružili najtačnije i najkorisnije činjenice, naših 10 najpopularnijih rezultata temelje se na kombinaciji podataka o programu ili velikim diplomama iz Nacionalnog centra za statistiku obrazovanja (NCES), primarnog federalnog entiteta za prikupljanje i analizu podataka koji se odnose na obrazovanju i popularnosti škole na našoj web stranici.


Primjena računarske i matematičke biologije na istraživanja genomike i genetike: pregled trendova i aktivnosti u akademskoj zajednici

Program za ljudski genom (HGP) će proizvesti ogromne količine informacija o sekvenci genomske DNK u narednih pet do deset godina. Biologima će ove informacije biti od male vrijednosti ako alati za upravljanje i tumačenje informacija nisu dostupni i nisu prilagođeni korisnicima. Kako bi se izradio plan kako će Nacionalni institut za istraživanje humanog genoma (NHGRI) osigurati da ti resursi budu na raspolaganju, vođeni su telefonski razgovori s približno 15 naučnika s iskustvom iz matematike, fizike, informatike, statistike, računarstva i molekularne biologije koji su također zabrinuti za ova pitanja. Od svih njih je zatraženo da opišu prepreke/ mogućnosti na koje bi NHGRI mogao djelovati pojedinačno ili u saradnji s drugim komponentama Nacionalnog instituta za zdravlje (NIH) ili privatnim odjelom. Identifikovano je pet oblasti: razvoj karijere infrastrukture, karijerni putevi u akademskoj istraživačkoj obuci i istraživanju. Osim toga, prepoznato je da i industrija ima veoma važnu ulogu u ovim oblastima. Stoga je dijalog sa liderima u akademskoj zajednici, industriji i vladi smatran prikladnim i pravovremenim. Na razmatranje su ponuđene sljedeće preporuke:

Infrastruktura

  1. Omogućite pojedincima na vodećim položajima u akademskim krugovima (provostore, kancelare, dekane i načelnike odjela/ odjela) da nauče više o širokom rasponu mogućnosti koje računska i matematička biologija predstavljaju u biologiji i medicini.

Razvoj kurikuluma
  1. Upotrijebite mehanizam za dodjelu nagrada za akademsku karijeru (K07) za podršku fakultetima u razvoju nastavnih planova i programa iz računskih i matematičkih nauka koji se odnose na genomiku i analizu genoma.
Obuka za razvoj karijere i istraživanje

  1. Razviti institucionalnu K01 programsku nagradu koja bi obezbijedila kritičnu masu nebiologa koji rade u oblastima računarske i matematičke biologije u institucijama u kojima postoje fokusi naučnika koji rade u interdisciplinarnim oblastima kritičnim za istraživanje genoma i analizu i interpretaciju genoma.

Istraživanje

  1. Procijenite zašto istraživački projekti u računskoj i/ili matematičkoj biologiji dobijaju loše ocjene prioriteta.

Outreach
  1. Sazovite lidere u industriji i akademskim krugovima radi rasprave o zajedničkim interesima i potrebama u istraživanju i obuci.

II. Pozadina

Program humanog genoma (HGP) proizvest će ogromne količine informacija o genomskoj DNK sekvenci. Upravljanje i tumačenje ovih informacija zahtijevat će 1) odgovarajuće analitičke metode, računarske alate i informacijske sisteme za prikupljanje, pohranu i distribuciju podataka o kartiranju i sekvenciranju i 2) obučeni kadar naučnika s interdisciplinarnim vještinama-oni koji razumiju biološki problem koji postoji i može pronaći rješenja primjenom vještina iz drugih disciplina. (3) Naučne discipline koje su ključne za upravljanje i tumačenje podataka o genomu uključuju računsku i matematičku biologiju i statistiku. U godišnjem izvještaju o napretku 1995-96, naglašena je potreba uspostavljanja bioinformatike kao struke. U dokumentu su identifikovani problemi u uspostavljanju nove profesije, kao što su „prihvatanje nove interdisciplinarne specijalnosti u akademskim institucijama (posebno u eri u kojoj resursi ne rastu) i dobijanje akademskog prihvatanja za aplikaciju orijentisanu (za razliku od teorije). -orijentisana) disciplina." Primijećeno je da je postignut određeni napredak u tome što nekoliko institucija počinje uspostavljati diplomske programe iz bioinformatike i uspjeh NHGRI -ove nagrade za istraživačku karijeru s posebnim naglaskom u podršci obuci nekoliko matematičkih i računskih biologa. Međutim, ti su napori neadekvatni s obzirom na to da se veliki napori u sekvenciranju genoma u modelnim organizmima i ljudima povećavaju brzinom koja će rezultirati desetinama do stotinama miliona informacija o parovima baza u bazama podataka o sekvencama. Ove će informacije imati malu vrijednost ako alati za upravljanje i tumačenje informacija nisu postavljeni i nisu prilagođeni korisnicima. Stoga su potrebne najmanje dvije vrste stručnjaka: 1) pojedinci sa solidnim iskustvom u matematičkim, fizičkim ili računarskim naukama, koji takođe imaju dovoljno znanja o biologiji da razumiju izazove i mogu razviti odgovarajuće analitičke metode i računarske alate i 2) biolozi koji razumiju pitanja koja se mogu riješiti ovim podacima i imaju temeljno utemeljenje u matematici, statistici ili računarstvu koji mogu razviti alate prilagođene korisnicima za opću upotrebu.

III. Metodologija

Telefonski sam intervjuisao pojedince navedene u Dodatku A. Većina osniva ili pokušava uspostaviti odjele, programe ili žarišta za računarsku ili matematičku biologiju u okviru svojih akademskih institucija. Svako je zamoljen da opiše svoju trenutnu situaciju, da se pozabavi da li postoji potreba za jačanjem računske ili matematičke biologije u akademskim krugovima, i ako jeste, koje su bile prepreke, koji modeli programa postoje i koji mehanizmi NIH-a osim grantova za institucionalnu obuku (T32) i nagradu za razvoj naučnika pod nadzorom (K01) trebalo bi razviti kako bi se povećao potencijal za uspostavljanje vidljivih i održivih programa ili odjela za računarsku i/ili matematičku biologiju ili odjela u akademskim krugovima.

Nacrt ovog izvještaja podijeljen je sa svim sagovornicima, a mnogi od njih su dali komentare. Većina prijedloga je uključena, međutim, autor ovog izvještaja preuzima punu odgovornost za njegov sadržaj. Autor također priznaje da je ovo odabrano, a ne statističko uzorkovanje stavova, pa neki prijedlozi i mišljenja mogu predstavljati pristrasnost ispitanika. Osim toga, mišljenja univerziteta (sa jednim izuzetkom) i lidera u industriji nisu zastupljena u ovom izvještaju.

Ovaj izvještaj je rezultat interne neformalne rasprave osoblja u oktobru 1996.

IV. Šta je potrebno

Ispitanici su identifikovali pet oblasti koje je potrebno razviti ili ojačati kako bi matematička i računarska biologija napredovala kao interdisciplinarna područja relevantna za istraživanja genomike/genetike u akademskim krugovima. To su infrastruktura, razvoj kurikuluma, razvoj karijere, istraživačka obuka i istraživanje. U nastavku je sažetak razgovora o svakoj od ovih oblasti.

Infrastruktura

Da bi nova disciplina uspjela u akademskim krugovima, ona mora imati intelektualnu i fiskalnu infrastrukturu u obliku odjela. Ovo je idealna situacija. Vjerovatno je tačna izjava da trenutno postoji vrlo malo odjela za računarsku ili matematičku biologiju u američkim institucijama. Utvrđeno je nekoliko prepreka za osnivanje odjela ili programa: 1) Većina akademskih institucija još uvijek nije prepoznala računsku i matematičku biologiju kao važna područja nauke u nastajanju vrijedna uzdizanja na odjel. 2) Primjena matematičkih ili informatičkih principa na biologiju je disciplina koja se širi i stvara interakcije između dvije discipline (biologija i matematičke ili računarske nauke) koje obično ne stupaju u naučnu interakciju i imaju tendenciju fizičkog i organizacionog razdvajanja. 3) Prilikom donošenja stalnih imenovanja za pojedince u interdisciplinarnom istraživanju, moraju se donijeti odluke o tome koji će se prostor odjela koristiti u vremenima kada je rast ograničen, što može otežati takve odluke i 4) Vrsta interdisciplinarnog istraživanja koja se provodi možda neće smatrati cijenjenim u primarnom odjelu. Na primjer, većina odjela za računarstvo i matematiku fokusira se na teorijska, a ne na primijenjena istraživanja.

Uprkos ovim preprekama, postoji nekoliko univerziteta koji su postigli određeni napredak u razvoju programa ili fokusa za matematičku i računarsku biologiju. Postoji nekoliko institucija u kojima je rukovodstvo prepoznalo važnost ove interdiscipline i formalno podržava ovaj napor (tj. pristup odozgo prema dolje). Neki primjeri su Centar za diskretnu matematiku i teorijske računarske nauke (DIMACS) (4) na Univerzitetu Rutgers i Kalifornijskom univerzitetu u Santa Cruzu, gdje je vodstvo interdisciplinarno istraživanje i bioinformatiku postavilo kao dio univerzitetskog strateškog plana. Odsjek za biomatematiku na Medicinskom fakultetu UCLA obučava studente doktorskih studija u različitim disciplinama, uključujući matematičku genetiku. Institut/centar na Univerzitetu Washington u St. ove institucije (tj. pristup odozdo prema gore). Potreba za postojanjem sistema za upravljanje informacijama za laboratorijsko upravljanje i tumačenje podataka bila je jezgra oko koje su ti programi uspostavljeni. Još jedan dogovor koji se pokazao produktivnim su trenutni dogovori na Univerzitetu Washington State i Univerzitetu Južne Kalifornije između visoko motiviranih pojedinačnih članova fakulteta na odsjecima za matematiku i biologiju koji rade sa diplomiranim studentima zainteresiranim za interdisciplinarne projekte (tj. ad hoc pristup). Dok je naučna disciplina vjerovatno bolje smještena u odjeljenju, iz gornjih primjera je jasno da univerziteti koriste druge mehanizme za razvoj međusobne povezanosti unutar disciplina izvan odjela kroz uspostavljanje centara, biroa i instituta.

Jedan sagovornik je upozorio na poteškoće u osnivanju novih odjela koji su spoj dvije ili više disciplina. Kontra argument je da ako se ne ulože napori u osnivanje novih odjela, u akademskim krugovima nikada ne bi bili uspostavljeni novi interdisciplinarni odsjeci. Alternativni i još uvijek koristan model je da diplomirani studenti ispune zahtjeve uspostavljene discipline/odsjeka, a zatim tu osnovu koriste za nastavak interdisciplinarnog projekta na drugom odjelu.

Iako su svi gore navedeni pristupi radili na obučavanju studenata na spoju biologije i matematičkih i računarskih nauka, oni su manje idealni i slabi su, ovisno o predsjedavajućim saradničkim odjelima i viziji budućnosti svakog univerziteta. Kako bi nova disciplina rasla i bila stabilna, postoje i drugi zahtjevi koji moraju nadopuniti akademsku strukturu-nastavni plan i program specifičan za tu disciplinu, priznati put u karijeri, kvalitetni studenti i resursi koji ih podržavaju te snažan istraživački program koji generiše nove pristupe i tehnologiju za novu disciplinu.

Razvoj kurikuluma

Nastavni plan i program je intelektualna osnova na kojoj se uspostavlja nova disciplina i integriraju novi koncepti iz različitih disciplina. U multidisciplinarnim područjima postoji tendencija da se od kandidata traži da nauče sve iz svih srodnih oblasti, a ne da sintetiziraju novi nastavni plan i program prilagođen potrebama nove discipline. Nedostatak nastavnog plana i programa za određenu disciplinu obično znači da će pojedincu trebati više vremena da ispuni uslove za diplomu. Shodno tome, studenti će biti manje privučeni da upišu studijski program koji zahtijeva dvostruke zahtjeve za kurs. Razvoj kurikuluma zahtijeva vrijeme koje većina nastavnika nije dala svojim predavačkim, istraživačkim, administrativnim/komitetskim i obrazovnim obavezama. Postoji nekoliko primjera gdje su pojedinci razvili nove interdisciplinarne tečajeve, ali zbog nedostatka vremena tečajevi, prema njihovom mišljenju, nisu toliko sveobuhvatni koliko je potrebno za stvarno prenošenje novih pristupa i koncepata. Svi ispitanici su bili mišljenja da bi mehanizam kojim bi se fakultetima dalo vrijeme da razviju odgovarajuće nastavne planove i programe i interdisciplinarne kurseve bio izuzetno koristan za ovu oblast i za obuku.

Putevi karijere u akademskim krugovima

Pojedinci obučeni za računarsku ili matematičku biologiju imaju nekoliko mogućnosti za zapošljavanje. Primarne dvije su industrija i akademija. Industrija nudi bolje mogućnosti i u smislu kompenzacije i karijere. Budući da je cilj u industriji proizvodnja proizvoda, pojedinci se zapošljavaju zbog svoje stručnosti kako bi obavili posao bez ograničenja potrebe da se prilagode zahtjevima kućnog odjela ili discipline. Karijera u akademskim krugovima je složenija, posebno za nove fakultete bez stalnog osoblja. Budući da su zaposleni, viši fakulteti mogu se baviti interdisciplinarnim istraživanjem jer su pokazali svoje sposobnosti u svojoj primarnoj naučnoj disciplini. Međutim, kako sve više univerziteta prepoznaje potrebu za poticanjem interdisciplinarnog istraživanja, to bi mogao postati manji problem za fakultete bez popunjenosti.

Jedna od briga diplomaca i postdoktoranata koji su zainteresovani za interdisciplinarna istraživanja jeste koje će ih akademsko odjeljenje zaposliti. Jedan od ispitanika predstavio je sljedeća dva primjera kako bi ilustrirao probleme sa kojima se mladi naučnici suočavaju. Prvi se odnosi na pojedinca čija je dodiplomska diploma iz biologije. Bavio se upotrebom računara u molekularnoj biologiji, stekao značajno iskustvo u ovoj oblasti, a sada želi da doktorira. Pitanje za njega je kako/gdje? Nakon dugih rasprava i traženja duše odlučio se za diplomu iz računarstva. Položio je uvjete za odsjeke i sada mora izabrati temu teze. On se bori s tim da li bi to trebao biti tradicionalni informatički projekt kako ga razumiju informatičari ili bi trebao biti relevantan za biologiju? Dilema je ono što može biti vrlo vrijedno istraživanje za biologe, i u izvesnom smislu inovativno, ne mora uključivati ​​nove teorijske koncepte u nova istraživanja računarstva. Prema riječima sagovornika, pojedinac još uvijek radi na ovim pitanjima i struktura odjela mu otežava donošenje odluke. Drugi slučaj je osoba sa dva doktora nauka, jednim iz matematike i jednim iz elektrotehnike/računarstva, koji sada radi na projektu vezanom za genom i bio je izuzetno produktivan. Želio bi ostati u akademskoj zajednici, ali ne kao naučni saradnik. On je odličan istraživač i bio bi koristan za mnoge programe. Problem je koji odjel? Može li se nadati da će dobiti imenovanje na odjelu za matematiku ili računarstvo koji će ga primiti da radi na razvoju algoritama u računarskoj biologiji? Iskustvo ovog ispitanika je da neće biti lako, ali planira učiniti sve što je potrebno kako bi pomogao ovoj osobi da osigura odgovarajuće akademsko mjesto na prvorazrednom univerzitetu. Ova dva slučaja ne bi bila problematična da je interdisciplinarno istraživanje prepoznato kao legitimno područje istraživanja bilo na odjelu biologije ili informatike.

Istraživačka obuka i razvoj karijere

Programi obuke pružaju akademsku strukturu pomoću koje diplomirani studenti i postdoktorandi uče temeljne naučne koncepte i imaju priliku provjeriti hipoteze kako bi povećali intelektualnu osnovu ovog područja. Sagovornici su se jednoglasno složili da je potrebno više pojedinaca obučiti kroz organizovane i dobro podržane programe istraživačke obuke. Postoje najmanje tri prepreke u osiguranju interdisciplinarnih grantova za obuku. Jedan je bio zahtjev da podnosilac zahtjeva ima dobro dokumentovane i uspostavljene odnose između fakulteta u odjelima koji sarađuju. Mnogi od ispitanika govorili su o poteškoćama novih programa obuke koji ispunjavaju ove uvjete podobnosti prvenstveno zbog količine vremena koje je potrebno da se fakulteti zainteresuju za druga odjeljenja da se zaista posvete interdisciplinarnim istraživanjima. Međutim, nakon što se članovi fakulteta uključe, obično zbog dodane vrijednosti vlastitog istraživanja, interakcije su vrlo produktivne za fakultete, studente i postdoktorande. Drugi je bio da su stipendije isplaćene nebiolozima bile znatno veće od stipendija koje se isplaćuju biolozima. Nivo stipendije za postdoktorande sa diplomama iz računarstva ili matematike sa manje od dvije godine iskustva kreće se između 35.000 i 42.000 dolara. Stipendije Nacionalne istraživačke službe za stipendiste kreću se od 20.292 do 32.300 dolara. Posljednja stopa je za postdoktorande koji imaju sedam ili više godina obuke nakon doktorske diplome. Stipendije za diplomirane studente iznose 11.496 USD. Ove stipendije su više usmjerene na podršku biologa, a ne nebiologa. Stoga je pokušaj privući nebiologe u programe obuke na ovim nivoima stipendija vrlo težak, ako ne i nemoguć. Treći je bio da nova politika NIH -a ograničava troškove školarine za stipendije za obuku (5) će otežati institucijama započinjanje novih ili održavanje postojećih programa obuke.

Još jedno područje diskusije bilo je ono što bi trebalo da bude dodiplomsko obrazovanje diplomiranih studenata obučenih iz računarske ili matematičke biologije. Mnogi ispitanici su smatrali da bi bilo poželjnije u ove oblasti zaposliti diplomirane studente sa preddiplomskim studijama matematike, statistike ili računarstva, a ne biologije. Razlog za ovo stajalište bio je taj što je teško utemeljenje matematičkih pojmova teško steći kasno u obrazovnom procesu. Takvi studenti bi dobili dovoljnu obuku (didaktičku i praktičnu) iz biologije, ali ne u istom intenzitetu kao što je to potrebno za diplomirane studente/postdoktorande iz biologije. Ponovo, naglasak bi bio na razvoju odgovarajućeg nastavnog plana i programa. Nisu svi intervjuisani bili saglasni oko vrste osnovnih studija neophodnih za računarsku ili matematičku biologiju. Primijećeno je da se izvrsnost može postići na mnogo načina i da je važna i perspektiva onih koji su obučeni za biologiju, ali koji su međusobno obučeni za matematičke i računarske nauke. Zapravo, mnogi od sadašnjih lidera u oblasti računarske i matematičke biologije danas su pojedinci čiji je doktorat u jednoj od specijalnosti iz biologije.

Jedan od sagovornika je sugerirao da se uloga matematike u biologiji proteže izvan HGP-a iu druge discipline u biologiji, te bi stoga druge komponente NIH-a također trebale razmotriti uspostavljanje interdisciplinarnih programa obuke. S obzirom na ulogu koju će matematika i računarska biologija imati u molekularnoj medicini, odnosno identifikaciju svih ili većine gena koji izazivaju bolest i jednog od nekoliko faktora uobičajenih bolesti, program obuke za doktorate/doktore znanosti također bi trebao proširiti mogućnosti obuke u ovim oblastima.

NHGRI -ova nagrada za istraživačku karijeru s posebnim naglaskom (K01) osnovana je 1991. godine za zapošljavanje pojedinaca sa formalnim obrazovanjem u matematici, računarstvu, hemiji, fizici i inženjerstvu za istraživanje genomike. Godišnje se dodijeli približno 3-4 nagrade. Svi nagrađeni imaju za mentore istraživače genoma. Većina ispitanika nije čula za ovaj program, ali su bili oduševljeni ovom vrstom nagrade, kao i nagradom institucijskog tipa koja bi podržala kritičnu masu pojedinaca da rade u projektima računarske ili matematičke biologije u njihovim institucijama.

Osoblje NHGRI izrazilo je zabrinutost da će se zbog potražnje i visokih plaća mnogi pojedinci koji su prošli obuku iz državnih fondova odlučiti za zaposlenje u industriji umjesto da ostanu u akademskim krugovima. Većina ispitanika to nije smatrala problemom. U mnogim slučajevima citirali su kolege kojima se povremeno nude unosnije pozicije u industriji, ali su se umjesto toga odlučili za akademsku slobodu, priliku za obuku studenata i sposobnost da se bave svojim istraživačkim interesom.

Istraživanje

Kako bi novo znanstveno područje uspostavilo intelektualnu neovisnost i bilo snažno u usavršavanju, neophodan je intenzivan, stabilan istraživački program. Nekoliko problema je identificirano kao prepreke za uspostavljanje istraživačkih projekata iz računske i matematičke biologije. Veliku zabrinutost predstavljala je naučna recenzija interdisciplinarnih projekata. Po mišljenju mnogih sagovornika, studijske sekcije u sadašnjem obliku nisu uvijek bile sposobne da pregledaju interdisciplinarne istraživačke projekte. Kratki projektni periodi su također smatrani ometajućim istraživačke aktivnosti. Za razvoj novih koncepata ili primjenu koncepata na nove probleme obično je potrebno više od dvije godine da se dokaže izvodljivost ili napredak. Trogodišnji grant u osnovi daje glavnom istražitelju otprilike dvije godine da pokaže uspjeh. Trogodišnji grant takođe otežava regrutovanje postdoktorskih saradnika za rad na projektu, zbog slabe podrške u narednim godinama. U nekoliko slučajeva, ispitanicima je rečeno da NIH institut/centar/odjel nije bio zainteresiran da podrži njihovo istraživanje u tom trenutku. Nakon kratke rasprave o njihovom predloženom istraživanju, osoblje NHGRI -a je zaključilo da se istraživanje čini primjerenim jednoj ili nekoliko komponenti NIH -a.

Jedan sagovornik je predložio da se sredstva koriste za podršku pojedincima kroz stipendije za istraživanje (R01) umjesto nagrada za razvoj istraživačke karijere (K). Obrazloženje je da pojedinci koji primaju podršku od plaće za razvoj karijere možda neće biti uspješni u dobivanju sredstava za recenziranje na kraju svog perioda dodjele, dok ako finansirate istraživačke projekte, glavni istraživač je pokazao svoj/njegov potencijal da generiše nova istraživanja. nalazi na terenu i istraživački projekt mogli bi poslužiti kao sredstvo za obuku diplomiranih studenata i postdoktoranata.

V. Uloga industrije

Većina intervjuisanih pojedinaca naglasila je važnost da industrija podrži, na suštinski način, razvoj i održavanje jakih fokusa računarske i matematičke biologije u akademskim krugovima iz nekoliko razloga. Prvo, industrija je bila veoma uspješna u regrutovanju obučenih pojedinaca na svim nivoima za rad u industriji. Kako se napori velikih razmjera genomskog sekvenciranja DNK povećavaju, postojat će sve veća potreba za pojedincima koji mogu upravljati i tumačiti podatke koji će biti platforma na kojoj se vode istraživanja u industriji u svrhu prevencije, liječenja i liječenja bolesti. Drugo, akademska zajednica je obično mjesto gdje se razvijaju inovativne, rizične tehnologije koje zatim koristi industrija. Oduzimanje obučenog osoblja iz akademskih krugova bez napora da se zamijeni i poveća broj pojedinaca uključenih u intelektualne aktivnosti na kraju će rezultirati gubitkom odgovarajućih ljudskih resursa za ishranu genetske revolucije. Stoga je potrebno da industrija sarađuje s akademskim krugovima kako bi osigurala da postoji dovoljno obučeno osoblje za razvoj novih znanja. Postoje neka komercijalna preduzeća koja doprinose ovom nastojanju, ali nivo predanosti i trajanje obaveze nisu poznati. Također, naglašeno je da industrijska sredstva trebaju biti neograničena kako bi se institucijama dala potrebna fleksibilnost da koriste sredstva za jačanje svojih istraživačkih napora gdje i kada je to prikladno.

VI. Šta je dostupno

Prije razvoja novih programa, važno je dokumentirati ono što je na raspolaganju i utvrditi postoje li modeli programa u računskoj i matematičkoj biologiji koji se trebaju replicirati. Sljedeća lista programa, iako nije reprezentativna za sve dostupne, vjerovatno predstavlja najveće napore u ovoj oblasti. Doprinosi iz industrije nisu prikazani jer nije bilo lakog načina za dokumentiranje ili utvrđivanje ovih podataka. Programi koji se mogu identificirati mogu se podijeliti u tri kategorije: 1) infrastruktura 2) razvoj karijere i 3) istraživačka obuka. Podrška ovim aktivnostima prvenstveno se pruža putem fondacija i savezne vlade.

Infrastruktura

Whitaker fondacija (6) [whitaker.org]
Nagrade za liderstvo Fondacije u biomedicinskom inženjerstvu obezbjeđuju sredstva institucijama sa odličnim obrazovnim programima u inženjerstvu ili medicini za uspostavljanje akademskih struktura (odjeljenja ili fizičkih struktura) za biomedicinsko inženjerstvo. Trajanje i iznos nagrade su fleksibilni, ali ovise o jednakoj ili većoj obavezi institucije podnositeljice zahtjeva. Nagrade za liderstvo bave se mogućnostima čiji su ciljevi ili potrebe za vanjskim finansiranjem izvan opsega dva postojeća programa.

Nagrade za razvoj biomedicinskog inženjeringa Fondacije osmišljene su za stvaranje centara izvrsnosti u obrazovanju o biomedicinskom inženjeringu uspostavljanjem ili poboljšanjem akademskih programa. Typical grants have three elements: a start-up award of up to $1 million (capital needs, such as renovations and laboratory enhancements), annual awards up to $500,000 for four years with an optional two-year extension (faculty salaries and graduate student support), and a continuation award of up to $1 million (strengthens the academic program). This award requires an affiliation between engineering programs and graduate or medical schools.

Career Development

The Charles E. Culpeper Foundation's Scholarships in Medical Science [goldmanpartnerships.org]
This program provides U.S. medical schools up to three years of support, on behalf of carefully selected physicians of high potential achievement who are committed to careers in academic medicine. Eligible disciplines are basic biomedical research with a special emphasis on molecular genetics, molecular pharmacology and bio-engineering. Provisions include $100,000 per year in direct cost to support salary (partial), research and travel expenses. Award is for three years.

National Human Genome Research Institute's Mentored Scientist Development Award [grants2.nih.gov]
The purpose of this K01 award (formerly known as the Special Emphasis Research Career Award) is to foster the career development of individuals with expertise in scientific disciplines (mathematics, chemistry, physics, engineering, and computer sciences) that would further technological developments critical to the success of the Human Genome Program. Provisions include: 1) annual salary up to $75,000 2) up to $20,000 for research-related expenses and 3) tuition. The duration of the award is three to five years. The number of awards made annually depends on the quality of the applications received.

Research Training

Burroughs Wellcome Fund's Interfaces between the Physical/Chemical/Computational Sciences and the Biological Sciences [bwfund.org]
The goals of this program are to break down the traditional barriers at academic institutions and to train investigators coming from quantitative and theoretical backgrounds so they can bring different approaches and new ideas into the biological arena. This is a program for degree-granting institutions to propose graduate or postdoctoral training programs, or a combination of both. Ancillary activities may include undergraduate student research programs, faculty seed grants, or invited lectures. Grants of $350,000 to $500,000 per year for five years are made to four to six U.S. and Canadian institutions.

Alexander Hollaender Distinguished Postdoctoral Fellowships [orau.gov]
This is a Department of Energy fellowship program to provide training in research areas of interest to the Office of Health and Environmental Research. Eligible disciplines are life, biomedical and environmental sciences and other supporting scientific disciplines. This is a one year fellowship renewable for a second year. The provisions are: beginning stipend of $37,500 and up to $2,500 to cover the cost of relocation.

Alfred P. Sloan Foundation and U. S. Department of Energy Postdoctoral Fellowships in Computational Molecular Biology [sloan.org]
The purpose of these fellowships is to catalyze career transitions into computational molecular biology from physics, mathematics, computer science, chemistry, and related fields. The program is designed to give computationally sophisticated young scientists an intensive postdoctoral opportunity in an appropriate molecular biology laboratory. This is a two year program with a total budget of $100,000 per awardee annually $42,000 is allotted for a stipend and $1,500 is allotted for research expenses. Up to ten fellowships are awarded annually.

The Whitaker Foundation Graduate Fellowship Program [whitaker.org]
This program supports students with engineering backgrounds to develop the skills required for a successful career in biomedical engineering. Awards are made for three years with an option to extend for up to two additional years. Provisions include a stipend of $17,000, a cost-of-education allowance of up to $13,500 and $1,500 for research-related fees. About 30 predoctoral fellowships are awarded annually.

National Science Foundation [nsf.gov]
The NSF has several training initiatives. The goal of the Integrative Graduate Education and Research Training Program is to enable the development of innovative, research-based, graduate education and training activities that will produce a diverse group of new scientists and engineers well-prepared for a broad spectrum of career opportunities. The emphasis is on critical and emerging areas of science and engineering. This is an institutional training grant provisions include 1) annual stipend of $15,000 per graduate student postdoctoral stipends are determined by the host institution 2) up to $200,000 for equipment and special purpose materials and 3) limited funds to defray the costs of research by students. Awards are made in amounts up to $500,000 annually, not including the maximum of $200,000 for equipment. Up to twenty awards will be made during the first three years of the program.

Several Directorates at NSF, Mathematical and Physical Sciences and Computer and Information Sciences and Engineering, support interdisciplinary training in the biological sciences.

Howard Hughes Medical Institute Graduate Fellowship Program [hhmi.org]
The purpose of this program is to promote excellence in biomedical research by helping prospective researchers with exceptional promise obtain a high quality graduate education. Several areas of training have been identified, including mathematical and computational biology. These awards are made for three years. Provisions include a stipend of $15,000 for the student and a $15,000 cost-of-education allowance for the institution. At least $2,200 of the latter must be used for the student's health insurance, books and supplies, computer and computer-related expenses, and travel to scientific meetings. Approximately 80 awards are made each year.

National Library of Medicine's Fellowship in Applied Informatics [nlm.nih.gov]
The purpose of the NLM Fellowship in Applied Informatics (F38) award is to provide individuals with various educational backgrounds ( scientific, clinical and administrative) the opportunity to apply the knowledge and technology of health informatics to help solve biomedical information management problems. Because NLM wishes to encourage applications from mid-career professionals as well as more junior applicants, the amount of the stipend is based on the salary or remuneration that the individual would have been paid by the home institution on the date of the award, but shall not exceed $58,000 per year. A $4,000 per year institutional allowance will be paid to defray the costs of supplies, equipment, travel, tuition, fees, insurance, and other trainee-related costs. The fellowship is limited to two years. This is a non-NRSA fellowship.

National Human Genome Research Institutes Institutional Training Grant in Genomic Sciences [grants1.nih.gov]
This is an institutional training program (T32) in genomic sciences to train scientists with multidisciplinary skills that will allow them to engage in research that will accomplish the goals of the Human Genome Program (HGP) and to take full advantage of the resulting genomic data and resources to solve biomedical problems and increase our understanding of human biology. This training program is intended to expand the research capabilities of individuals with backgrounds in either molecular biology or a nonbiological scientific discipline relevant to genomic sciences (e.g., physical, chemical, mathematical, computer or engineering sciences). Provisions include: 1) annual stipends-$11,496 for graduate students and $20,292-$32,300 for postdoctoral fellows 2) tuition and 3) partial support of research-related expenses annually-up to $1,500 per year per graduate student and up to $2,500 per year per postdoctoral trainee. The number of grants awarded annually depends on the quality of the applications received. Duration of the institutional awards is up to five years individuals are usually supported for two to three years under this mechanism. This is a National Research Service Award and as such, the provisions are determined by the NIH.

VII. Preporuke

The following recommendations are distilled from the discussions with the interviewees. Staff suggests that these recommendations serve as the starting point of a discussion with leaders in academia, industry and non-profits. There are clearly some areas where new mechanisms can be established, but the success of computational and mathematical biology depends upon developing a strategy in which all parties that have a collected vested interest in the area are brought together to discuss what needs to be done, who will/can do what, and how resources can be leveraged, once there has been an agreement that an opportunity exists to provide stable support to a new discipline.

Infrastructure

  1. Provide opportunities for individuals in leadership positions in academia (Provosts, Chancellors, Deans, and Department/ Division Heads) to learn more about the broad range of opportunities that computational and mathematical biology present in biology and medicine. Presentations at annual meetings of professional societies (such as the Society for Industrial and Applied Mathematics, Pacific Symposium on Biocomputing, etc) and the American Association of Medical Colleges by members who are working at the interface of biology and mathematics or computer science would be one way to discuss the opportunities this interdiscipline provides to the future of biology and medicine.

Curriculum Development
  1. Use the academic career award (K07) mechanism to support faculty to develop curricula in computational and mathematical sciences as they relate to genomics and genome analysis. Curricula should be developed for students at the undergraduate and graduate levels.
Career Development and Research Training

  1. Develop an institutional K01 program award that would provide a critical mass of non-biologists working in the areas of computational and mathematical biology in institutions where there are foci of scientists working in interdisciplinary areas critical to genome research and genome analysis and interpretation.

Istraživanje

  1. Evaluate why research projects in computational and/or mathematical biology receive poor priority scores.

Outreach
  1. Convene leaders in industry and academia to discuss common interests and needs in research and training.
Immediate Action Items

  1. Develop brochures about NHGRIs training and career development opportunities.

Appendix Interviewees

Russ B. Altman, MD, Ph.D. (Medical Information Sciences)
Assistant Professor of Medicine and (Computer Science by courtesy)
Department of Medicine (Department of Computer Science by courtesy)
Medicinski fakultet Univerziteta Stanford
Stanford, CA

Michael Boehnke, Ph.D. (Biomathematics)
Professor
Department of Biostatistics
School of Public Health
University of Michigan
Ann Arbor, MI

Dan Davison, Ph.D. (Biological Sciences-Genetics)
Principal Scientist
Bioinformatics Department
Bristol-Myers Squibb Pharmaceutical Company
Wallingford, CT

Keith A. Dunker, Ph.D. (Biophysics)
Professor
Departments of Biochemistry and Biophysics, Chemistry
Washington State University
Pullman, WA

Philip Green, Ph.D (Mathematics)
Vanredni profesor
Molecular Biotechnology Department
Univerzitet Washington
Seattle, WA

David Haussler, Ph.D. (Computer Science)
Professor, Computer Information Science
Division of Natural Science
University of California
Santa Cruz, CA

Edward Holmes, MD
Senior Associate Dean for Research and
Vice President for Translational Medicine and Clinical Research
Medicinski fakultet Univerziteta Stanford
Stanford, CA

Webb Miller, Ph .D. (Mathematics)
Professor
Department of Computer Science
Pennsylvania State University
University Park, PA

Chris Overton, Ph.D. (Biophysics), MSE (Computer Science)
Director, Center for Bioinformatics
University of Pennsylvania
Philadelphia, PA

Neil Risch, Ph.D. (Biomathematics)
Professor
Department of Genetics
Medicinski fakultet
Stanford University
Stanford, CA

Fred Roberts, Ph.D. (Mathematics)
Professor of Mathematics
Director, Center for Discrete Mathematics and Theoretical Computer Science
Rutgers University
Piscataway, NJ

Temple Smith, Ph.D. (Physics)
Direktor
BioMolecular Engineering Research Center
College of Engineering
Bostonski univerzitet
Boston, MA

Terence P. Speed, Ph.D. (Mathematics)
Professor
Department of Statistics
Kalifornijski univerzitet, Berkeley
Berkeley, CA

David States, MD, Ph.D. (Biophysics)
Direktor
Institute for Biomedical Computing
Medicinski fakultet
Washington University
St. Louis, MO

Gary Stormo, Ph.D. (Molecular Biology)
Vanredni profesor
Department of Molecular, Cellular and Developmental Biology
University of Colorado
Boulder, CO

Clark Tibbetts, Ph.D. (Biophysics/Chemistry)
Professor of Microbiology
Institute for Molecular Bioscience and Technology
George Mason University
Fairfax, VA

Michael Waterman, Ph.D. (Statistics)
Professor
Department of Mathematics (Joint Appointments in Biological Sciences and Computer Sciences

Fusnote

  1. This review was initially focused on bioinformatics. During the course of my interviews, it was expanded to include the application of mathematics, statistics, and computer science to genomics and genetics research. Thus, the title, while not ideal, is meant to be inclusive, rather than exclusive, of these scientific disciplines.


Major exploration course(s) added by advisors for incoming first-year students

Biomathematics Major Exploration Course(s) recommended by faculty. At least one of these will be included in your Fall schedule:

Students with a Precalculus or Calculus math placement AND Expository Writing English placement

Course Title

Course Number

Students without a Precalculus or Calculus math placement AND Expository Writing English placement

Course Title

Course Number


How to learn biomathematics? - Biologija

Need Help? Mathematic Tutorials

An Introduction to Scientific Notation A quick review of writing very large and very small numbers using scientific notation.

Mathematical Notation Learn the proper notation for representing numbers, sets, sums, and products.

Introduction to Functions Learn the definition and properties of functions, how to perform mathematical operations on functions, and then practice what you have learned.

Transformations Learn how functions are transformed and how to sketch the graph of a function by inspecting the equation. Then test your knowledge.

Linear Functions Learn the definition of linear function, how to calculate the slope of a line, how to solve a linear equation, and how linear models are used in biology. Then practice what you have learned.

Quadratic Functions Learn the definition of a quadratic function, what the graph of quadratic function looks like,and how to solve quadratic equations. Then test your knowledge with a problem set.

Exponential Functions Learn the definitions of exponential functions, how they are graphically represented, and how to graph basic exponential functions and transformed exponential functions.

Logarithmic Functions Learn the definitions of logarithmic functions and their properties, and how to graph them. Then practice what you have learned with exponential and logarithmic functions.

Polynomials Learn the definition of a polynomial, how to perform polynomial division, and what a graph of a polynomial function looks like. Then review what you have learned with a problem set.

Power Functions Learn the definition of a power function and how to graph one. Then test your knowledge with a problem set.

Rational Functions Learn the definition of a rational function, what the graph of a rational function looks like, and how to find the asymptotes. Then complete the problem set.

Trigonometric Functions Learn the definition of a trigonometric function, review some special angles, learn what the graphs of various trigonometric function look like, and see some trigonometric identities. Then test your knowledge with a problem set.

Shodor Activities designed for either group or individual exploration into concepts from middle school mathematics. The activities are Java applets and as such require a java-capable browser.

Powers of Ten A travel across the Universe. Changing scale by just a few powers of ten dramatically alters your perspective.

Cyberchase A PBS website for kids of all ages with math games and web adventures.


Please note that the TRACS information about some of our courses is outdated. The information that appears above is more reliable, and if there is any question over course content or prerequisites, please contact the course instructor.

Abbreviations used for cross-listed courses are as follows: MA – Mathematics, OR – Operations Research, and ST – Statistics. An example of credit information is: 4(3-2). The 4 indicates the number of semester hours credit awarded for successful completion of the course. The (3-2) indicates that the course normally meets for three hours of lecture and two hours of problem session per week. The abbreviations F, S, and Sum indicate courses normally offered in the fall and spring semester and in the summer terms, respectively.

BMA 567 Modeling of Biological Systems.
Prereq: 1 semester of calculus (e.g., MA 112) 4(3-2) F. An introduction to quantitative modeling in biology. Compartment models, Forrester diagrams, probabilistic and deterministic descriptions of dynamic processes, development of model equations, simulation methods, criteria for model evaluation. Readings from current literature on applications of modeling and simulation in biology. Laboratory sessions emphasize the scientific computing skills used in biological modeling. An individual modeling project, preferably related to the student’s research interests, is required.

BMA 610 Special Topics.
Offered from time to time during Fall or Spring semesters.

BMA (ST, MA) 771 Biomathematics I.
Preq.: Advanced calculus (including matrix algebra) and reasonable background in biology, or consent of the Instructor. 3(3-0)F. Mathematical methods for dynamic state variable models in biomathematics, especially difference and differential equations, with applications including models for population dynamics, pattern formation, and enzyme kinetics. Emphasis is placed on determining the qualitative behavior of solutions rather than on explicit solutions or numerical computation.

BMA (ST,MA) 772 Biomathematics II.
Prereq.: BMA 771, elementary probability theory. 3(3-0)S. Continuation of BMA 771. Methods for analyzing nonlinear models, concepts of local and global stability, periodic and non-periodic solutions. Comparison of deterministic and stochastic models. Survey of applications and some discussion of recent research.

BMA (ST,OR,MA) 773 Stochastic Modeling.
Prereq.: BMA 772 or ST 746. 3(3-0) F. Survey of modeling approaches and analysis methods for data from continuous state random processes. Emphasis on differential and difference equations with noisy input. Doob-Meyer decomposition of process into signal and noise components. Examples from biological and physical sciences, and engineering. A student project is required. (Offered F 2000 and alt. years.)

BMA (MA,OR) 774 Partial Differential Equation Modeling in Biology.
Prereq.: BMA 771 or MA/OR 731 BMA 772 or MA 401 or MA 501 3(3-0)S. Modeling with and analysis of partial differential equations as applied to real problems in biology. Review of diffusion and conservation laws. Waves and pattern formation. Chemotaxis and other forms of cell and organism movement. Introduction to solid and fluid mechanics/dynamics. Introductory numerical methods. Scaling. Perturbations, Asymptotics, Cartesian, polar and spherical geometries. Case studies.

BMA 801 Biomathematics Graduate Seminar.
Prereq.: Grad standing 1(1-0) F, S. Student and faculty presentations of current research in biomathematics. Purposes are to broaden perspective on the field of biomathematics and research opportunities, and to give students practice in seminar presentation. Students make one presentation per year. For Ph.D. candidates, two of these presentations must concern thesis research, one near the start of the work, and the other near the completion of the thesis. Attendance is required.

BMA 815 Advanced Special Topics.
Offered from time to time in the Fall and Spring semesters.


University Admission Requirements

A student applying to a master's program must:

  • have earned a four-year bachelor's degree or its equivalent from a college or university that is accredited by the appropriate regional accrediting association, or do so within one academic year
  • present unofficial transcripts from each college or university other than Illinois State at which graduate, undergraduate, or non-degree credit was earned. The unofficial transcript should be easily readable and clearly indicate degree(s) awarded, courses and course grades for each term. If accepted, official transcripts can be emailed from the university to [email protected] or mailed in a sealed envelope to: Graduate School, 209 Hovey Hall, Campus Box 4040, Normal, IL 61790-4040.

International students can learn more about specific application requirements by visiting the Office of Admissions.

Additional Program Admission Requirements

Lab Requirement

The first step in the application process is to ask about working in a lab. We do not admit graduate students unless they have at least one faculty member who is willing to have them in their lab.

Contact a member of our faculty who works in your area of interest. Discuss whether they are taking new students, whether your interests sufficiently overlap with theirs, and what research topics are being pursued in their labs.

You must have a 3.0 on a 4.0 scale for the last 60 hours of undergraduate coursework or any previous work in a master’s program.

Curriculum Vitae or Resume

Submit your vita in the application system. It should include any information that will help assess your potential as a student in our graduate program. Also include:

  • your educational background
  • previous employment or positions related to science and your current status
  • research activities, including publications
  • memberships in professional societies
  • any honors and awards you have received

Statement of Academic and Professional Goals

Write a one-to-two page statement of your academic and professional goals and submit it in the application system.

Your statement should include:

  • area of research in which you are interested
  • faculty member(s) with whom you have corresponded in regard to serving as your possible dissertation advisor
  • your plans after completing graduate school

Letters of Recommendation

Provide three letters of recommendation. Your letters should be from faculty members or others who are familiar with your academic record and can evaluate your potential for graduate study.

Test Scores

GRE scores are not required for your application. However, if you wish to submit them, you may.

Scores do not play a significant part in our decision-making process for admission. GRE scores may help your application if you did not have strong undergraduate grades but have strong GRE scores.

Use institution code 1319 if you want to submit your scores. It will not be held against you if you do not submit GRE scores as part of your application.

International students required to take an English proficiency test must have a TOEFL score of 90 or greater. The IELTS equivalent is approximately 6.5.

Application Deadlines

  • Fall (August) Term &mdash February 1
  • Spring (January) Term &mdash Not accepting applications
  • Summer Term &mdash Not accepting applications

Connect with cutting-edge research under the microscope or out in the field

Research Opportunities
Students are required to complete an independent research project under the supervision of a faculty member (either math or biology) and present their research in the Biomathematics Seminar.

Center for the Sciences and Innovation (CSI)
Trinity’s integrated, 300,000-square-foot science and engineering complex contains glass-walled laboratories, classrooms, and offices that put science on display. CSI supports teaching and research in biomathematics in addition to multiple fields of biology, chemistry, and mathematics, among others.

Undergraduates also have the opportunity to learn and perform a variety of modern research techniques such as chromatography, electrophoresis, phase contrast and fluorescent microscopy, tissue culture, electrophysiology, confocal microscopy, and ultracentrifugation.


Integrative Biomathematical Learning Alliance Across Academic Departments

Across the nation, many generalized programs have focused on retention of minority students in the sciences with varying degrees of success. Paradoxically, this challenge exists despite expanding career opportunities in industry, academia, and government for those skilled at the intersection of biology and mathematics. Here I describe a cross-departmental learning alliance (iBLEND- an Integrative Biomathematics Learning and Empowerment Network for Diversity) which directly targets these recognized challenges. Our goal is for the iBLEND project to have significant spillover effects for our university by developing new interdisciplinary collaborations that benefit our students. The iBLEND is a proactive, intensive approach in order to bridge campus chasms for both faculty and undergraduate students by positively influencing academic programs through interdisciplinary training coupled with strong evaluation and assessments. By leveraging our recent surge of competitive research activity, innovative instruction, and collaboration, the iBLEND advances our transformation to the next level by establishing a broader bridge for our undergraduates at the interface of mathematics and biology. In working together, the math and biology students learned to bridge language barriers inhibiting interdisciplinary explorations. Students are closely involved with faculty mentors in core laboratories and developed cross-disciplinary research skills that enhanced their post-graduate career opportunities. Using systems biology tools combined with targeted mathematics classroom work, students merge data from their lab bench experiments with mathematical models to determine how various changes impacted an overall organism and its functions. The students have hands-on training with a myriad of computational, simulations, data mining and data analysis tools needed in approaching their projects.

TARGETED STUDENT PARTICIPANTS AT A CRITICAL TRANSITION POINT
North Carolina Agricultural and Technical State University (NCATSU) is a historically minority-serving land-grant institution with an overall enrollment of approximately 11,000 undergraduates. Currently, the Biology Department has over 500 majors and the Mathematics Departments has over 100 majors. Undergraduates in both departments are over 90% African American representing a diverse talent pool for broadening participation in science. Although NCATSU is the largest Historically Black College and University (HBCU) in North Carolina, we are aware that overcoming under-representation in biology and mathematics is difficult. For instance, given the mission as a land grant HBCU, our entering freshman are admitted having a wide-range of prior high school success. Too many NCATSU freshmen exhibit deficits in critical thinking and writing, as compared to underrepresented as compared to the percentage of undergraduates at majority institutions who go on to pursue freshmen at other institutions participating in the same study. These data are routinely disseminated as evidence in multiple ways to faculty, highlighting the need for excellent teaching, strong interdisciplinary training, and high-quality biomathematics-related research. We focus iBLEND activities relative to deep learning that crosses beyond conventional boundaries between biology, mathematics, computer science, physics and chemistry disciplines.

INNOVATIVE STRATEGIES TO BRIDGE THE GAPS AT THE MATH-BIO INTERFACE
Our integrative model not only raises the bar for the incoming high-performing students, but seeks avenues that can amplify the overall supply of students who emerge from NCATSU on a competitive trajectory for biomathematical graduate study. Innovative to our approach is that all of the research projects bring undergraduate researchers to our centrally located Molecular Genetics, Genomics, and Proteomics Laboratory and the Applied Mathematics Modeling Laboratory. The purpose of our core lab is to provide interdisciplinary research and training for both undergraduates and faculty. The core laboratories include biologists, mathematicians, and computational bio-physicists, from each of the basic science departments involved in laboratory research. This shared space provides natural opportunities for our undergraduates to fuse conceptual understanding between research and classroom activity. We have found that the core labs provide iBLEND a supportive dynamic sphere for high expectations and academic challenges for our undergraduates. We believe shared spaces are essential to provide natural opportunities for undergraduates to fuse conceptual understanding between research and classroom activity. Hence iBLEND takes full advantage of the capabilities of our newly established Molecular Biology Core Laboratory. The core laboratories also serve as a training ground for faculty to learn new techniques. Ramifications from this research are particularly well-suited for spirited discussion and debate that further establish meaningful relationships between mathematics and biology. The strong interdisciplinary research projects and training are built on research strengths of faculty in the Departments of Biology and Mathematics enriched with collaborations with neighbor Research-1 institutions. The central geographic location of NCATSU between Wake Forest Univ., UNC-Chapel Hill, Duke Univ., and NC State Univ., and other institutions provides easy implementation for several day visits and field trips during the academic semesters with collaborating laboratories on our project.

The iBLEND research and training are coupled with mechanisms that reduce barriers to student success. As many of our students are first generation college attendees, there is a wealth of life experiences and personal connections to these projects that give real-world research purpose and provide students with every opportunity to succeed in biomathematics. The lab research described above is specifically designed to overcome pre-conceived notions concerning advanced mathematics or computationally-rich courses. This is particularly true for minority students where underrepresentation in research careers goes back to a complex interplay of socio-economic forces that impact academic achievement. Used appropriately, mathematical models can represent pathways in a physically and biologically realistic manner and generate novel and useful hypotheses. The modeling intellectual focus and tools span the range from prediction to identification of mechanistic structures. This research theme is specifically structured to complement the individual strengths and circumstances of each research mentor. Students gain a better understanding of the governing processes at the molecular, cellular, and organismal level through mathematical analysis of the overall dynamical system models and various numerical methods and simulations. The student iBLEND intellectual focus is on the development of mathematical skills in set theory, linear algebra, differential equations, number theory, numerical analysis, stochastic and deterministic processes, topology, and computational mathematics. This aids in the development of analytical argumentative strategies to better understand high-throughput biological data which includes molecular genetics, host-pathogen microbiology, comparative and functional genomics, phylogenetics, plant physiology, ecology, and genomic instability and oncology.

KEY ORGANIZATIONAL STRUCTURE AND INSTITUTIONAL ENDORSEMENTS
Because of the many positive impacts, some even beyond intended project goals, iBLEND has significant buy-in from administration, faculty, and students. We gain buy-in from stakeholders by: (1) working from the ground-up with administration to promote campus-wide biomathematics research and training (2) fostering associations between research and regular undergraduate academic courses (3) creating and disseminating biomathematics teaching and learning modules and (4) enhancing learning community support at the interface of mathematics and biology. Since 2006, NCATSU has hired many new faculty with significant biomathematical research portfolios to share with undergraduates in iBLEND. Hence, we have a solid cadre of faculty and staff pursuing research and shared discovery at the interface of mathematics and biology, and all are part of this proposed work.

These measures that have increased undergraduate research and research training included:
-Collective math-biology departmental faculty conceptualization and crafting of grant proposals
-Emphasis on faculty and student development in research and pedagogy
-Provision of collaborative math-biology departmental retreats to foster new ideas
-Emphasis on freshman orientations specific for biology and math majors
-Distribution of bio-math shared documents through centralized computer servers
-Broadening team-taught bio-math courses and research contributions
-Providing a weekly bio-math seminars and annual bio-math scientific research symposia