Now accepting applications for Systems Scientist, Assistant Teaching Professor, Postdoc, and Masters Students
The Lane Center for Computational Biology is currently accepting applications for a Systems Scientist, Assistant Teaching Professor, Postdoctoral Researcher, and students for the M.S. in Biotechnology Innovation and Computation program.
Lane Faculty Member Wins Teaching Award
Asst. Teaching Prof. Karen Thickman has been selected as one of the 2012-2103 Wimmer Faculty Fellows at the Eberly Center for Teaching Excellence. This program is designed for junior faculty members interested in enhancing their teaching through concentrated work with an Eberly consultant. The Wimmer program, now in its seventh year, is supported by a grant from the Wimmer Family Foundation. This grant provides a stipend to each Fellow to acknowledge the intellectual work it takes to be an effective educator. We congratulate Karen and thank her for her excellent work with students in the Lane Center and throughout Carnegie Mellon!
Lane Student and Faculty Member help link sirtuin protein to longevity in mammals
Ph.D. student Guy Zinman and his advisor Ziv Bar-Joseph are among the authors of a paper in Nature that for the first time links overexpression of a gene called sirtuin 6 to increased life span in mammals, specifically mice. Researchers who study aging have been intrigued by the large family of sirtuin genes and their proteins ever since they were linked to longevity in yeast.
Lane Center Faculty Member wins Overton Prize for outstanding accomplishment
The International Society for Computational Biology (ISCB) has awarded its Overton Prize for outstanding accomplishment to Ziv Bar-Joseph, associate professor in Carnegie Mellon University’s Lane Center for Computational Biology and Machine Learning Department.
The Overton Prize is awarded annually to an early- to mid-career scientist who has made a significant contribution to the field of computational biology. In recognition of the award, Bar-Joseph will give a keynote address this July at the annual International Conference on Intelligent Systems for Molecular Biology (ISMB) in Long Beach, Calif.
Bar-Joseph applies machine learning, statistical algorithms and signal processing techniques to the analysis of high-throughput biological data. He has led international research efforts that have identified genes important to human cell division, including a subset associated with cancer cells, which have uncovered new insights into gene regulatory networks.
Lane Center Faculty Team With Ion Torrent to Develop Open Source Software to Interpret Personal Genomic Information
Ion Torrent announced today a new generation of sequencing instrument that will enable sequencing of a personal genome for $1,000. This will dramatically increase the number of individual genomes available for finding associations between sequence and disease, and Ion Torrent also announced that they are sponsoring a collaborative effort with the Lane Center to develop open-source software to help clinicians interpret personal genome sequences. Collaborators at Baylor College of Medicine and Yale Medical School will obtain genome sequences and clinical parameters to help train the system.
“The huge variation in human genome sequence between individuals has always been an obstacle to understanding how to use sequence information to improve human health,” said Dr. Robert F. Murphy, director of the Lane Center for Computational Biology in Carnegie Mellon’s School of Computer Science, who will lead the multidisciplinary CMU team. “We believe new machine learning approaches will enable interpretation of personal genome sequences to help doctors diagnose and guide treatment in the near future.”
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Ray and Stephanie Lane Center for Computational Biology
The Lane Center for Computational Biology at Carnegie Mellon University seeks to realize the potential of machine learning for expanding our understanding of complex biological systems. A primary goal of the center is to develop computational tools that will enable automated creation of detailed, predictive models of biological processes, including automated experiment design and data acquisition. We anticipate that these efforts will not only lead to deep biological knowledge but also to tools for individualized diagnosis and treatment of cancer and other diseases. The Lane Center builds on the strong history of computational and interdisciplinary research at Carnegie Mellon.