The Lane Center for Computational Biology is seeking outstanding researchers who are developing computational methods in all areas of biology for tenure-track, research and teaching positions at all levels. Applications for the Lane Fellows Program are now being accepted. Read more...
Kumar et al. identify potential cancer biomarkers via image analysis
The Murphy group published a paper with implications for cancer research today in the U.S. Proceedings of the National Academy of Sciences. It describes a new method for identifying proteins that differ significantly in subcellular location between normal and cancerous tissue and applies it to images of four human tissues from the Human Protein Atlas. The proteins identified may help improve cancer detection and diagnosis, and may increase our understanding of the oncogenic process.
Roeder and Autism Sequencing Consortium Identify 33 Genes That Contribute to Autism Risk
The list of genes identified with autism spectrum disorder (ASD) by deep DNA sequencing has expanded from nine to 33, according to a new study by an international research team led by the Autism Sequencing Consortium (ASC), including the Lane Center’s Kathryn Roeder.
Published in Nature, the study examined data on several types of rare, genetic differences in more than 14,000 DNA samples from parents, affected children and unrelated individuals. It is the largest sample to date, and provides evidence that small differences in some of possibly 1,000 risk genes contribute to autism. In addition to increasing the number of definitive autism genes almost fourfold, the team pinpointed more than 70 other likely ASD genes.
The genes identified involve critical brain processes, apparently affecting the formation of nerve networks and altering the function of synapses, the crucial structures that allow brain cells to communicate.
"This makes sense because typical development of brain cells require intricate coordination among thousands of genes and appropriate communication between cells to ensure development of the brain - the most complicated organ in the human body," said Roeder, a leading expert on statistical genomics and the genetic basis of complex disease. Read More…
Kingsford receives Moore Foundation "Big Data" Grant for Biomedical Sequence Analysis
Associate Professor of Computational Biology Carl Kingsford has been selected as one of 14 recipients of the Gordon and Betty Moore Foundation's "Moore Investigators in Data Discovery" awards. The unrestricted award of $1.5 millon will support Kingsford's efforts to develop efficient new methods for searching the massive amounts of DNA and RNA sequencing data now available world wide. Read more...
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.