Literature DB >> 27897014

THE TRAINING OF NEXT GENERATION DATA SCIENTISTS IN BIOMEDICINE.

Lana X Garmire1, Stephen Gliske, Quynh C Nguyen, Jonathan H Chen, Shamim Nemati, John D VAN Horn, Jason H Moore, Carol Shreffler, Michelle Dunn.   

Abstract

With the booming of new technologies, biomedical science has transformed into digitalized, data intensive science. Massive amount of data need to be analyzed and interpreted, demand a complete pipeline to train next generation data scientists. To meet this need, the transinstitutional Big Data to Knowledge (BD2K) Initiative has been implemented since 2014, complementing other NIH institutional efforts. In this report, we give an overview the BD2K K01 mentored scientist career awards, which have demonstrated early success. We address the specific trainings needed in representative data science areas, in order to make the next generation of data scientists in biomedicine.

Entities:  

Mesh:

Year:  2017        PMID: 27897014      PMCID: PMC5425257          DOI: 10.1142/9789813207813_0059

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  14 in total

1.  Infodemiology and infoveillance tracking online health information and cyberbehavior for public health.

Authors:  Gunther Eysenbach
Journal:  Am J Prev Med       Date:  2011-05       Impact factor: 5.043

2.  Opinion: Big data biomedicine offers big higher education opportunities.

Authors:  John Darrell Van Horn
Journal:  Proc Natl Acad Sci U S A       Date:  2016-06-07       Impact factor: 11.205

Review 3.  Mining electronic health records: towards better research applications and clinical care.

Authors:  Peter B Jensen; Lars J Jensen; Søren Brunak
Journal:  Nat Rev Genet       Date:  2012-05-02       Impact factor: 53.242

4.  Emergence of Narrowband High Frequency Oscillations from Asynchronous, Uncoupled Neural Firing.

Authors:  Stephen V Gliske; William C Stacey; Eugene Lim; Katherine A Holman; Christian G Fink
Journal:  Int J Neural Syst       Date:  2016-07-14       Impact factor: 5.866

5.  A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer.

Authors:  Sijia Huang; Cameron Yee; Travers Ching; Herbert Yu; Lana X Garmire
Journal:  PLoS Comput Biol       Date:  2014-09-18       Impact factor: 4.475

6.  mirMark: a site-level and UTR-level classifier for miRNA target prediction.

Authors:  Mark Menor; Travers Ching; Xun Zhu; David Garmire; Lana X Garmire
Journal:  Genome Biol       Date:  2014       Impact factor: 13.583

7.  The golden era of biomedical informatics has begun.

Authors:  Jason H Moore; John H Holmes
Journal:  BioData Min       Date:  2016-04-11       Impact factor: 2.522

Review 8.  Adapting bioinformatics curricula for big data.

Authors:  Anna C Greene; Kristine A Giffin; Casey S Greene; Jason H Moore
Journal:  Brief Bioinform       Date:  2015-03-30       Impact factor: 11.622

Review 9.  Single-Cell Transcriptomics Bioinformatics and Computational Challenges.

Authors:  Olivier B Poirion; Xun Zhu; Travers Ching; Lana Garmire
Journal:  Front Genet       Date:  2016-09-21       Impact factor: 4.599

10.  Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis.

Authors:  Sijia Huang; Nicole Chong; Nathan E Lewis; Wei Jia; Guoxiang Xie; Lana X Garmire
Journal:  Genome Med       Date:  2016-03-31       Impact factor: 11.117

View more
  4 in total

Review 1.  Using 'collective omics data' for biomedical research training.

Authors:  Damien Chaussabel; Darawan Rinchai
Journal:  Immunology       Date:  2018-05-30       Impact factor: 7.397

2.  Democratizing data science through data science training.

Authors:  John Darrell Van Horn; Lily Fierro; Jeana Kamdar; Jonathan Gordon; Crystal Stewart; Avnish Bhattrai; Sumiko Abe; Xiaoxiao Lei; Caroline O'Driscoll; Aakanchha Sinha; Priyambada Jain; Gully Burns; Kristina Lerman; José Luis Ambite
Journal:  Pac Symp Biocomput       Date:  2018

3.  Prediction of Tuberculosis Using an Automated Machine Learning Platform for Models Trained on Synthetic Data.

Authors:  Hooman H Rashidi; Imran H Khan; Luke T Dang; Samer Albahra; Ujjwal Ratan; Nihir Chadderwala; Wilson To; Prathima Srinivas; Jeffery Wajda; Nam K Tran
Journal:  J Pathol Inform       Date:  2022-01-20

4.  Patient insights on features of an effective pharmacogenomics patient portal.

Authors:  Tien M Truong; Elizabeth Lipschultz; Emily Schierer; Keith Danahey; Mark J Ratain; Peter H O'Donnell
Journal:  Pharmacogenet Genomics       Date:  2020-12       Impact factor: 2.000

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.