Translational bioinformatics applications in genome medicine

Although investigators using methodologies in bioinformatics have always been useful in genomic experimentation in analytic, engineering, and infrastructure support roles, only recently have bioinformaticians been able to have a primary scientific role in asking and answering questions on human health and disease. Here, I argue that this shift in role towards asking questions in medicine is now the next step needed for the field of bioinformatics. I outline four reasons why bioinformaticians are newly enabled to drive the questions in primary medical discovery: public availability of data, intersection of data across experiments, commoditization of methods, and streamlined validation. I also list four recommendations for bioinformaticians wishing to get more involved in translational research.

[1]  D. Mccormick Sequence the Human Genome , 1986, Bio/Technology.

[2]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[3]  S. P. Fodor,et al.  Using oligonucleotide probe arrays to access genetic diversity. , 1995, BioTechniques.

[4]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[5]  International Human Genome Sequencing Consortium Initial sequencing and analysis of the human genome , 2001, Nature.

[6]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[7]  P. Brown,et al.  Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Ian H. Witten,et al.  Data mining in bioinformatics using Weka , 2004, Bioinform..

[9]  M. Linscheid,et al.  Quantitative proteomics , 2005, Analytical and bioanalytical chemistry.

[10]  Atul J. Butte,et al.  Evaluation and integration of 49 genome-wide experiments and the prediction of previously unknown obesity-related genes , 2007, Bioinform..

[11]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[12]  Dennis B. Troup,et al.  NCBI GEO: mining tens of millions of expression profiles—database and tools update , 2006, Nucleic Acids Res..

[13]  Joel Dudley,et al.  Enabling Integrative Genomic Analysis of High Impact Human Diseases Through Text Mining , 2007, Pacific Symposium on Biocomputing.

[14]  Atul J Butte,et al.  The Ultimate Model Organism , 2008, Science.

[15]  Douglas G Altman,et al.  Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets , 2008, PLoS medicine.

[16]  Scott McMillan,et al.  Keeping pace with the data: 2008 update on the Bioinformatics Links Directory , 2008, Nucleic Acids Res..

[17]  Michael Y. Galperin,et al.  Nucleic Acids Research annual Database Issue and the NAR online Molecular Biology Database Collection in 2009 , 2008, Nucleic Acids Res..