Tenure-track and Research-track Faculty Positions Available
The Lane Center for Computational Biology is seeking outstanding researchers who are developing computational methods in all areas of biology for tenure-track and research-track positions at all levels. Read more...
CPCB graduate Joshua Kangas featured in SLAS
While still a student, Joshua Kangas, Ph.D., made a life-changing decision. Instead of moving along his planned career path in education, he decided to partner with science and business experts to launch a company that would help enhance the efficiency of drug discovery efforts. Read more...
MSBIC student Jing Li selected as 2014 James R. Swartz Entrepreneurial Fellow
Jing Li is one of 10 CMU students in Carnegie Mellon selected for this fellowship, which fast-tracks the careers of selected graduate students who are passionate about entrepreneurship in the technology arena. The program will help develop their potential and leadership skills through hands-on experiences, networking, mentoring and courses in entrepreneurship. Jing will receive a summer internship at a top-tier venture-backed startup, travel stipend for two treks to Silicon Valley and mentoring by CIE faculty and staff, venture capitalists, and C-level executives in high-tech companies in California's Silicon Valley.
Roeder leads study that finds genetic risk for autism stems mostly from common genes
Lane Center and Statistics Professor Kathryn Roeder has led an international team of researchers who discovered that most of the genetic risk for autism comes from versions of genes that are common in the population rather than from rare variants or spontaneous glitches. Read more...
Lane Center personnel lead team discovering new method to dramatically speed up estimates of gene expression
Lane Center faculty member Carl Kingsford and postdoctoral researcher Rob Patro, along with Stephen M. Mount of the University of Maryland, published a paper in Nature Biotechnology on April 20 describing a new method for quickly estimating gene expression from RNA-seq data. By avoiding the slow step of read mapping, their approach can produce accurate estimates of 15-20 times faster than previous approaches. This speed will be essential for mining the many terabytes of sequence data now available, for expanding the number of samples that can be considered when trying to understand the function of particular genes, and for widespread clinical use of RNA-seq-based diagnostics. Read more...
Computer Analyzes Massive Clinical Databases To Properly Categorize Asthma PatientsCarnegie Mellon computational biologist Wei Wu says a computer program, capable of tracking more than 100 clinical variables for almost 400 people, has shown it can identify various subtypes of asthma, which could lead to targeted, more effective treatments. MORE
Lane Center featured in Biophysical Society video
The MMBioS center, a collaboration between the University of Pittsburgh, Pittsburgh Supercomputing Center, Salk Institute and Carnegie Mellon was featured in a video created by the Biophysical Society for the 'Biophysical Society TV' shown at their annual meeting. The Technology Research and Development project (TR&D3) being led by Dr. Murphy is described starting at 4:18.
CMU's iGEM Team Successful Again - Accepting Applications for Next Year's Team!
The Carnegie Mellon iGEM2013 Team traveled to Toronto to compete in the North American iGEM Team Competition and returned with the Best Poster Award. The Poster titled “Light-Activated Antimicrobial Phage” was one of 64 presented by teams that attended the Regional Jamboree. Team members Kathy Bates (BME/ChemE 2013), Ben Beltzer (CompBio 2016), Andrew Nadig (Bio2015), Eric Pederson (Bio 2015), and Evan Starkweather (ChemE 2015) tackled the problem of antibiotic resistance with an alternative, phage therapy. The bacteriophage that they designed had a secret weapon, it could be activated by light to kill bacteria. The team was generously supported by the Lane Center for Computational Biology, MCS and the Department of Biological Sciences, CIT and the Departments of BME, ChemE and ECE.
We are now accepting applications for the Carnegie Mellon iGEM2014 Team. The iGEM Team is a team of undergraduates interested in synthetic biology (see here for more information). The team will conceive and complete a project and participate in the International Genetically Engineered Machines Competition at the World Jamboree in Boston from October 30 – November 3, 2014.
There will be Info sessions on Wednesday and Thursday January 29 and 30 at the UC Dowd Room, 4:30pm refreshments and 5pm presentation. Applications consist of the student’s resume and a one page description of why they are interested in iGEM and how they would contribute to the team. These items are to be sent to Dr. Natasa Miskov-Zivanov, email@example.com, by February 10th, 2014.
This is a competition where every project is an invention! The interdisciplinary team will identify a problem and a need, design and build a prototype from standard biological parts (this is Synthetic Biology), and then share their project with the community. The core values of effort, accomplishment, respect, cooperation and especially scientific integrity and truth are promoted and achievements are celebrated at the World Jamboree.
The project of interest is designed, planned and managed by the team members with advisors serving to provide guidance. In the lab, the parts are cloned, combined, tested, documented and submitted to the Registry. Models of the system or device are developed and validated with lab results. Human Practices are designed to communicate the synthetic biology project. Skills are developed for communication of projects using wikis, posters and oral presentations.
This is a great opportunity to work with an interdisciplinary team, receive a stipend and academic credit, and participate in the World Jamboree!
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.