alexa Reproducibility In Biomedical Sciences - Big Data Perspective
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
Open Access

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9th International Conference on Structural Biology
September 18-20, 2017 Zurich, Switzerland

Wladek Minor
University of Virginia, USA
Keynote: J Proteomics Bioinform
DOI: 10.4172/0974-276X-C1-099
Abstract
Experimental reproducibility is the cornerstone of scientific research, upon which all progress rests. The veracity of scientific publications is crucial because subsequent lines of investigation rely on previous knowledge. Several recent systematic surveys of academic results published in biomedical journals reveal that a large fraction of representative sets of studies in a variety of fields cannot be reproduced in another laboratory. Big Data approach and especially NIH Big Data to Knowledge (BD2K) program is coming to the rescue. The goal of the presented research is to provide the biomedical community with a strategy to increase the reproducibility of reported results for a wide range of experiments by building a set of best practices, culled by extensive data harvesting and curation combined with experimental verification of the parameters crucial for reproducibility. Experimental verification assisted by the automatic/semi-automatic harvesting of data from laboratory equipment into the already developed sophisticated laboratory information management system (LIMS) will be presented. This data in, information out paradigm will be discussed.
Biography

Wladek Minor is a Harrison Distinguished Professor of Molecular Physiology and Biological Physics at University of Virginia. He is an expert in Structural Biology and Data Mining. He is an author of over 190 papers that attracted over 37,000 of citations. His relative citations ratio is above 560. He trained over 80 scientists who currently pursue career in academia, government and industry.

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