Literature DB >> 27447037

Unraveling the Complexities of Life Sciences Data.

Roger Higdon1,2,3,4, Winston Haynes1,2,3,4, Larissa Stanberry1,2,3,4, Elizabeth Stewart1,4, Gregory Yandl1,2,4, Chris Howard4,5, William Broomall2,3,4, Natali Kolker2,3,4, Eugene Kolker1,2,3,4,6.   

Abstract

The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (Data-Enabled Life Sciences Alliance, DELSAglobal.org), the Kolker Lab ( kolkerlab.org ) is creating partnerships that identify data challenges and solve community needs. We specialize in solutions to complex biological data challenges, as exemplified by the community resource of MOPED (Model Organism Protein Expression Database, MOPED.proteinspire.org ) and the analysis pipeline of SPIRE (Systematic Protein Investigative Research Environment, PROTEINSPIRE.org ). Our collaborative work extends into the computationally intensive tasks of analysis and visualization of millions of protein sequences through innovative implementations of sequence alignment algorithms and creation of the Protein Sequence Universe tool (PSU). Pushing into the future together with our collaborators, our lab is pursuing integration of multi-omics data and exploration of biological pathways, as well as assigning function to proteins and porting solutions to the cloud. Big data have come to the life sciences; discovering the knowledge in the data will bring breakthroughs and benefits.

Year:  2012        PMID: 27447037     DOI: 10.1089/big.2012.1505

Source DB:  PubMed          Journal:  Big Data        ISSN: 2167-6461            Impact factor:   2.128


  7 in total

1.  MOPED enables discoveries through consistently processed proteomics data.

Authors:  Roger Higdon; Elizabeth Stewart; Larissa Stanberry; Winston Haynes; John Choiniere; Elizabeth Montague; Nathaniel Anderson; Gregory Yandl; Imre Janko; William Broomall; Simon Fishilevich; Doron Lancet; Natali Kolker; Eugene Kolker
Journal:  J Proteome Res       Date:  2013-12-18       Impact factor: 4.466

Review 2.  The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders.

Authors:  Roger Higdon; Rachel K Earl; Larissa Stanberry; Caitlin M Hudac; Elizabeth Montague; Elizabeth Stewart; Imre Janko; John Choiniere; William Broomall; Natali Kolker; Raphael A Bernier; Eugene Kolker
Journal:  OMICS       Date:  2015-04

3.  Precision omics data integration and analysis with interoperable ontologies and their application for COVID-19 research.

Authors:  Zhigang Wang; Yongqun He
Journal:  Brief Funct Genomics       Date:  2021-07-17       Impact factor: 4.840

4.  Integrative analysis of longitudinal metabolomics data from a personal multi-omics profile.

Authors:  Larissa Stanberry; George I Mias; Winston Haynes; Roger Higdon; Michael Snyder; Eugene Kolker
Journal:  Metabolites       Date:  2013-09-03

5.  Beyond protein expression, MOPED goes multi-omics.

Authors:  Elizabeth Montague; Imre Janko; Larissa Stanberry; Elaine Lee; John Choiniere; Nathaniel Anderson; Elizabeth Stewart; William Broomall; Roger Higdon; Natali Kolker; Eugene Kolker
Journal:  Nucleic Acids Res       Date:  2014-11-17       Impact factor: 16.971

6.  The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR.

Authors:  Daniel Wibberg; Bérénice Batut; Peter Belmann; Jochen Blom; Frank Oliver Glöckner; Björn Grüning; Nils Hoffmann; Nils Kleinbölting; René Rahn; Maja Rey; Uwe Scholz; Malvika Sharan; Andreas Tauch; Ulrike Trojahn; Björn Usadel; Oliver Kohlbacher
Journal:  F1000Res       Date:  2019-11-07

7.  CIDO, a community-based ontology for coronavirus disease knowledge and data integration, sharing, and analysis.

Authors:  Yongqun He; Hong Yu; Edison Ong; Yang Wang; Yingtong Liu; Anthony Huffman; Hsin-Hui Huang; John Beverley; Junguk Hur; Xiaolin Yang; Luonan Chen; Gilbert S Omenn; Brian Athey; Barry Smith
Journal:  Sci Data       Date:  2020-06-12       Impact factor: 6.444

  7 in total

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