Event Abstract Back to Event Data Integration from Genome to Phenotypes Shankar Subramaniam1* 1 University of California at San Diego, United States We are witnessing the emergence of the “data rich” era in biology. The myriad data in biology ranging from sequence strings to complex phenotypic and disease-relevant data pose a huge challenge to modern biology. The standard paradigm in biology that deals with “hypothesis to experimentation (low throughput data) to models” is being gradually replaced by “data to hypothesis to models and experimentation to more data and models”. And unlike data in physical sciences, that in biological sciences is almost guaranteed to be highly heterogeneous and incomplete. In order to make significant advances in this data rich era, it is essential that there be robust data repositories that allow interoperable navigation, query and analysis across diverse data, a plug-and-play tools environment that will facilitate seamless interplay of tools and data and versatile user interfaces that will allow biologists to visualize and present the results of analysis in the most intuitive and user-friendly manner. This talk with address several of the challenges posed by enormous need for scientific data integration in biology with specific exemplars and possible strategies. The issues addressed will include: - Architecture of Data and Knowledge Repositories - Databases – Flat, Relational and Object-Oriented; what is most appropriate? - The imminent need for Ontologies in biology - The Middle Layer: How to design it? - Applications and integration of applications into the middle layer - Reduction and Analysis of Data – the largest challenge! - How to integrate legacy knowledge with data? - User Interfaces: web browser and beyond The complex and diverse nature of biology mandates that there is no “one solution fits all” model for the above issues. While there is a need to have similar solutions across multiple disciplines within biology, the dichotomy of having to deal with the context, which is everything in some cases, poses severe design challenges. For example, can a system that describes cellular signaling also describe developmental genetics? Can the ontologies that span different areas (e.g. anatomy, gene and cellular biology, functional imaging) be compatible and connective? Can the detailed biological knowledge accrued painstakingly over decades be easily integrated with high throughput data? These are only few of the questions that arise in designing and building modern data and knowledge systems. Conference: Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009. Presentation Type: Oral Presentation Topic: Keynote speakers Citation: Subramaniam S (2019). Data Integration from Genome to Phenotypes. Front. Neuroinform. Conference Abstract: Neuroinformatics 2009. doi: 10.3389/conf.neuro.11.2009.08.126 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 10 Jun 2009; Published Online: 09 May 2019. * Correspondence: Shankar Subramaniam, University of California at San Diego, San Diego, United States, shankar@ucsd.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Shankar Subramaniam Google Shankar Subramaniam Google Scholar Shankar Subramaniam PubMed Shankar Subramaniam Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.