Adapting bioinformatics curricula for big data
Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are ch...
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| Vydáno v: | Briefings in bioinformatics Ročník 17; číslo 1; s. 43 - 50 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
England
Oxford Publishing Limited (England)
01.01.2016
Oxford University Press |
| Témata: | |
| ISSN: | 1467-5463, 1477-4054, 1477-4054 |
| On-line přístup: | Získat plný text |
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| Abstract | Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. |
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| AbstractList | Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. |
| Author | Greene, Casey S. Moore, Jason H. Greene, Anna C. Giffin, Kristine A. |
| Author_xml | – sequence: 1 givenname: Anna C. surname: Greene fullname: Greene, Anna C. – sequence: 2 givenname: Kristine A. surname: Giffin fullname: Giffin, Kristine A. – sequence: 3 givenname: Casey S. surname: Greene fullname: Greene, Casey S. – sequence: 4 givenname: Jason H. surname: Moore fullname: Moore, Jason H. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25829469$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1093/nar/gks1174 10.1136/amiajnl-2014-002974 10.1093/bioinformatics/14.7.549 10.1016/j.jbi.2006.02.008 10.1093/bib/4.1.7 10.1136/amiajnl-2012-001053 10.1038/nmeth.1923 10.1038/nmeth.1828 10.1002/hyp.5801 10.1187/cbe.13-10-0193 10.1038/gim.2013.72 10.1145/1536616.1536632 10.1126/scitranslmed.3002648 10.1016/j.jbi.2006.02.005 10.1038/nature09534 10.1093/bib/bbn006 10.1145/2500499 10.1038/509S66a 10.1187/cbe.10-03-0038 10.1371/journal.pbio.1001745 10.1371/journal.pcbi.1003089 10.1038/nature.2014.16014 10.15265/IY-2014-0018 10.1038/nature.2014.16015 10.1371/journal.pone.0016461 10.1038/nbt.2514 10.1038/81541 10.1093/nar/gkq537 10.1371/journal.pcbi.1002957 10.1126/scitranslmed.3001318 10.1038/498255a 10.1093/bib/bbt023 10.1371/journal.pgen.1000407 10.1086/296148 10.1371/journal.pcbi.1003496 10.1186/1471-2164-10-S3-S36 |
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| Keywords | education data science big data bioinformatics |
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| Title | Adapting bioinformatics curricula for big data |
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