PNAS paper published by Jun Li, Assistant Professor, Human Genetics and Assistant Research Professor, Computational Medicine and Bioinformatics and colleagues, on circadian rhythm disruption in depression.
"Every cell in our bodies runs on a 24-hour clock, tuned to the night-day, light-dark cycles that have ruled us since the dawn of humanity. The brain acts as timekeeper, keeping the cellular clock in sync with the outside world so that it can govern our appetites, sleep, moods and much more.
But new research shows that the clock may be broken in the brains of people with depression -- even at the level of the gene activity inside their brain cells.
It’s the first direct evidence of altered circadian rhythms in the brain of people with depression, and shows that they operate out of sync with the usual ingrained daily cycle. The findings, in the Proceedings of the National Academy of Sciences, come from scientists from the University of Michigan Medical School and other institutions."
Bioinformatics graduate Alum Gang Su recently published the book "Instant Cytoscape Complex Network Analysis How-to" and it is currently available on Amazon.com.
"This book is great for people who have basic knowledge of programming, network analysis, and Cytoscape usage but would like to visualize and explore some network data. Readers are expected to know the basic concepts of network data, and be capable of using text editing software to edit tabular data which is imported into Cytoscape. Optionally, the user should understand network clustering and command line tools such as R."
"Dr. Arul Chinnaiyan has been selected to receive the Distinguished University Innovator Award for 2013.
The award honors faculty who have made important and lasting contributions to society by developing novel ideas and insights through their research, and then translating them to practice.
Chinnaiyan is the S.P. Hicks Endowed Professor of Pathology, professor of urology, director of the Michigan Center for Translational Pathology, and a Howard Hughes Medical Institute investigator. He is being honored for his work as a researcher, innovator, and entrepreneur in the field of molecular pathology.
“Arul Chinnaiyan’s work shows how critical university research is to the development of new ways to diagnose and treat disease,” said Vice President for Research Steve Forrest. “It also highlights the key role of technology licensing and entrepreneurship in moving new ideas quickly and effectively from the laboratory to practice.”
An internationally recognized scholar, Chinnaiyan found in 2005 that a majority of prostate cancers harbor gene fusions or translocations, shedding new light on our understanding of the molecular basis of prostate cancer and laying the groundwork for new diagnostic tests and therapies. Since that landmark discovery, gene fusions also have been discovered in lung cancer, colon cancer, breast cancer and others.
Chinnaiyan’s work has led to 75 new invention disclosures resulting in 12 patents, and six license and option agreements. Products arising from these licenses already are reaching the marketplace in the form of new diagnostic tests for prostate cancer.
In addition to licensing technology, Chinnaiyan has founded three companies. Compendia Biosciences, founded in 2006, was based on a cancer genomics research database now used by a range of pharmaceutical and biotechnology companies. More recently, he formed Armune Bioscience Inc. to develop and commercialize new diagnostic tests for prostate, lung, and breast cancers.
And in 2012 he joined with Shaomeng Wang, Warner-Lambert/Parke-Davis Professor of Medicine, and professor of internal medicine, pharmacology, medicinal chemistry, to found OncoFusion Therapeutics Inc., a company that aims to develop personalized cancer therapies based on the specific driving genetic mutations in an individual’s tumor.
Established in 2007, the Distinguished University Innovator Award recipient is chosen by the vice president for research on the recommendation of a faculty selection committee, which reviews a pool of nominees each year. The recipient is honored in a public ceremony and delivers a lecture focusing on the innovative work that led to the award.
This year’s award ceremony and lecture will take place at 4 p.m. April 30 in the Ford Amphitheater at University Hospital with a reception to follow in the Ford Lobby."
The Bioinformatics Program wishes to congratulate Shanshan Cheng, a recipient of the 2013 EDGE Award.The Endowment for the Development of Graduate Education (EDGE) Award provided financial support to 4 senior graduate students in the Basic Sciences for the 2013-2014 academic year.The Program is proud that Shanshan Cheng, Ph.D. candidate, was among those selected. Ms. Cheng studies biomolecules through molecular dynamics simulation. Her advisor is Prof. Charles Brooks III.
AMIA (American Medical Informatics Association)
2013 Joint Summits on Translational Science
San Francisco California
Parc 55 Hotel San Francisco
Tuesday, March 19
TBI-04: Panel - tranSMART: An Open Source and Community-Driven Informatics and Data Sharing Platform for Clinical and Translational Research
8:30 AM - 10:00 AM; Cyril Magnin I (Parc 55 Wyndham San Francisco)
B. Athey, University of Michigan; M. Braxenthaler, Pistoia Alliance; M. Haas, One Mind for Research; Y. Guo, Imperial College London
tranSMART is an emerging global open source public private partnership community developing a comprehensive informatics-based analysis and data-sharing cloud platform for clinical and translational research. The tranSMART consortium includes pharmaceutical and other companies, not-for-profits, academic entities, patient advocacy groups, and government stakeholders. The tranSMART value proposition relies on the concept that the global community of users, developers, and stakeholders are the best source of innovation for applications and for useful data. Continued development and use of the tranSMART platform will create a means to enable “pre-competitive” data sharing broadly, saving money and, potentially accelerating research translation to cures. Significant transformative effects of tranSMART includes 1) allowing for all its user community to benefit from experts globally, 2) capturing the best of innovation in analytic tools, 3) a growing ‘big data’ resource, 4) convergent standards, and 5) new informatics-enabled translational science in the pharma, academic, and not-for-profit sectors.
TBI Poster Session
5:00 PM - 6:00 PM; Cyril Magnin Foyer (Parc 55 Wyndham San Francisco)
AMIA-069-T2013. tranSMART PostgreSQL Collaborative Effort
Terry Weymouth; Glenn Tarcea; Manish Kapoor; John Boles; Mark Conser; Jonathan Cornibe; Michael McDuffie; Jean Avitabile; Jinlei Liu; Kevin Smith; Brian Athey
We report on a collaborative effort to port tranSMART from Oracle to postgreSQL. The tranSMART platform accelerates discoveries within complex biological systems by supporting an integrated database of research results linked to reusable and scalable analytics; postgreSQL is a premiere open source database system. The porting effort further expanded tranSMART’s reach into the open source world. The effort demonstrated the feasibility of open source development and collaboration that brings together private and public interests.
AMIA-109-T2013. Integrating NCIBI Tools into tranSMART
Terry Weymouth; Zach Wright; Vasudeva Mahavisno; Glenn Tarcea; Alex Ade; Maureen Sartor; Alla Karnovsky; Kevin Smith; Brian Athey
The tranSMART open source data-sharing and analytics platform provides search, browse, and exploration capabilities of heterogeneous data in support of clinical and translational research. We ported a set of richly interactive tools from the National Center for Integrative Biomedical Informatics (NCIBI) project into the search portion of tranSMART. These tools support the linking of user data with NCIBI integrated pathway, genetics, metabolomics, MeSH, and PubMed data. Both a learning experience and a typical development effort, this project contributed enhanced analytical capabilities to tranSMART.
tranSMART Community Meeting
6:30 p.m. – 8:00 p.m. Mission (Parc 55 Wyndham San Francisco)
Want to know more about tranSMART? Come learn about the Open Source and Community-Driven Informatics and Data Sharing Platform for Clinical and Translational Research. Updates on major projects and the tranSMART roadmap will be presented. Connect with newbie and veteran members of the tranSMART community.
The Bioinformatics Program congratulates Ph.D. candidates Mallory Freeberg and Bo Li!
They are both recipients of the Rackham Predoctoral Fellowship for next year. This prestigious fellowship supports graduate students in their final stages of academic study. The Rackham Graduate School states explicitly that this fellowship is “to support students working on dissertation that are unusually creative, ambitious and risk-taking.”
Complete information can be found here:
"Sofia Merajver will receive the MICHR Distinguished Translational Mentor Award on March 15 at 9:30 a.m. in the Alumni Center (during the MICHR Symposium).
She was nominated for the 2013 MICHR Distinguished Clinical and Translational Mentor Award by her peers and mentees and was selected from a highly competitive pool.
MICHR has established this award in order to recognize and honor the efforts and accomplishments of faculty who demonstrate consistent, high quality research and career mentoring in areas of clinical and translational and health research.
This award recognizes the value to the University of Michigan in assisting junior investigators to reach across disciplinary boundaries in pursuit of science. It also recognizes the important role mentoring plays in ensuring the personal and professional development of a mentee. This award is part of MICHR’s continuing efforts to foster a culture of mentoring plays in ensuring the personal and professional development of a mentee. This award is part of MICHR’s continuing efforts to foster a culture of mentoring, especially in the area of clinical and health research."
U-M researchers use new technique to shed light on RNA
" When researchers sequence the RNA of cancer cells, they can compare it to normal cells and see where there is more RNA. That can help lead them to the gene or protein that might be triggering the cancer.
But other than spotting a few known instigators, what does it mean? Is there more RNA because it’s synthesizing too quickly or because it’s not degrading fast enough? What part of the biological equilibrium is off?
After more than a decade of work, researchers at the University of Michigan Comprehensive Cancer Center have developed a technique to help answer those questions."
"The University of Michigan Health System has earned a $9.1 million core grant from the National Institutes of Health to improve disease diagnosis through metabolic profiling.
With the support, the U-M will create the Michigan Regional Comprehensive Metabolomics Research Core, one of only three centers in the country that will help researchers examine small molecules called metabolites to detect changes in cell behavior and organ function.
Burant who is experienced in metabolomics, diabetes and obesity research is the principal investigator of the grant, with Stephen Brown, Ph.D., serving as program coordinator of the new regional metabolomics research core. Several University of Michigan investigators will lead additional components of the core including Robert Kennedy, Ph.D., Hobart H. Willard Professor of Chemistry; Subramanian Pennathur, M.B.B.S., associate professor of internal medicine; Brian Athey, Ph.D., chair of the Department of Computational Medicine and Bioinformatics; Naisyn Wang, Ph.D., professor of statistics, and Barbara Mirel, Ph.D., associate research scientist at the School of Education. Grace Wu will serve as administrator."
M. L. Wynn, N. Consul, S. D. Merajver and S. Schnell (2012). Logic-based models in systems biology: a predictive and parameter-free network analysis method. Integrative Biology 4, 1323-1337.
In the above paper, Wynn et al shows how parameter-free logic-based models are intuitive, predictive, and robust tools for qualitatively describing the integration of complex biochemical interactions without prior knowledge of mechanistic details of molecular networks. Logic models can provide robust predictions of emergent behaviors in networks and can be used to help biomedical scientists unravel fundamental properties of molecular networks.