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Computational reproducibility should be relatively straightforward to achieve at the time of publication, but experience has shown that most research groups struggle with it. I will discuss the increasingly rich (and unfortunately) complex ecosystem of tools in this area, and show how we are mixing open science approaches with fairly simple tools to drive replication and encourage reuse/remixing of our research software. Bio: While Titus has many diverse research interests, a goal of his lab is to combine computation with experiment in order to improve our understanding of gene function. The development and extension of data analysis tools and toolkits is also an increasingly large interest of his lab. His group works across developmental biology, molecular biology, bioinformatics, metagenomics and next-generation sequencing. Titus has been an advocate of open-source software and open science for decades, and he is committed to using novel computer science tools to explore large genomic sequencing data sets. Titus holds a PhD from the California Institute of Technology, and he will be moving to UC Davis in January 2015, where he will lead the Laboratory of Data Intensive Biology. Speaker: Dr. C. Titus Brown, Michigan State University / University of California at Davis. Title: Openness and Reproducibility in Computational Science: Tools, Approaches, and Thought Patterns. Date: October 17th, 2014