April 16, 2009 | Dana-Farber Launches Computational Services Center
Dana-Farber launched a computational biology center this week to deliver analytical services and accelerate 'omics research. Investigators in basic, clinical, and translational research now have access to expert data analysis and interpretation services at one of the region's top research organizations: the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute.
"As technology has matured and our ability to generate biological data has improved, the question has increasingly become how to turn data in knowledge and knowledge into understanding," says CCCB director John Quackenbush, PhD, of the Department of Biostatistics and Computational Biology at Dana-Farber and professor of Computational Biology and Bioinformatics at Harvard School of Public Health. "Our goal is to provide the infrastructure necessary to address the needs of ‘omic scientists and to establish the capacity to tackle the next generation of questions arising from the application of new technologies across the range of biological research."
The Center offers a wide range of analytic services for a number of different types of data, including gene expression, copy number variation, ChIP-Seq, SNP, and next-generation DNA sequencing data, among others. Examples of the type of projects with which the CCCB can provide assistance are the identification and validation of novel gene signatures, integration of clinical and demographic information with 'omic data, identification of patterns of chromosomal abnormalities, and discovering of promoters and regulators of gene expression.
The Center maintains an extensive scientific computing infrastructure that includes a high performance computer cluster, large capacity data storage arrays, and high availability clustered Oracle database systems. These resources allow the CCCB to offer support for basic scientific computing needs such as web development and custom scientific software development to more complex problems that include clinical data modeling and warehousing and relational database design, implementation, and support. More information on CCCB services and capabilities can be found at http://cccb.dfci.harvard.edu.
GenoLogics Teams with Applied Biosystems
GenoLogics will provide an integrated lab and data management solution for its next generation advanced genomic analysis platform, the SOLiD System. "Our relationship with GenoLogics helps ensure that scientists using the SOLiD System are fully supported with an end-to-end lab and data management solution, enabling efficient management of their growing volumes of next-generation sequencing data," said Roger Canales, Applied Biosystems' Senior Manager of the SOLiD Software Development Community. Read release.
GNS Enters Brain Cancer Research Collaboration with M.D. Anderson
Gene Network Sciences entered into a research collaboration with The University of Texas M.D. Anderson Cancer Center aimed at the rapid translation of DNA sequence and clinical data from patients with glioblastoma into breakthrough discoveries leading to drugs and diagnostics. This collaboration will leverage the genetic data and clinical oncology expertise from M.D. Anderson with supercomputers and advanced machine-learning software from GNS. Financial terms of the agreement were not disclosed.
The rich glioblastoma dataset produced by M.D. Anderson researchers, which includes genetic, genomic, and clinical endpoint data (“3-D Data”), will be analyzed using GNS’s supercomputer-driven REFS(TM) (Reverse Engineering and Forward Simulation) software platform. These analyses are expected to generate models that enable the discovery of key genes, proteins and other molecular entities that together, as a network, causally drive glioblastoma disease progression, disease recurrence, and survival. The results from these projects will include the identification of new combination drug targets for disease and the development of diagnostics to determine appropriate individual patient treatments.
Separately, GNS announced Eric Schadt, a leading researcher in the field of genomics-driven drug discovery, will co-chair the GNS Scientific Advisory Board. Schadt is leaving his position as Executive Scientific Director of Genetics at pharmaceutical giant Merck to join forces with the departing head of Merck oncology Stephen Friend, to create Sage, an open-access distributed data platform designed to enable collaboration by integrating the myriad of genomic data sets in the public and private domains. Schadt is also an Affiliate Professor in the Department of Biostatistics at the University of Washington in Seattle, and he was recently appointed as a Fellow in the Institute of Synthetic and Systems Biology at Imperial College London. Schadt’s co-chair is James Collins of Boston University.
Codon Devices Closing as Financing Dwindles
Codon Devices, a five-year-old Boston synthetic biology company co-founded by George Church and Drew Endy, is quietly shutting down. Read Boston Globe article.
ISB Researchers Report New Powerful Algorithm
“Until recently, genetics has been practiced mainly as the study or identification of this gene or that gene which is then linked to a specific disease,” says ISB Associate Professor Timothy Galitski, PhD. “Technological and computational advances are allowing us to look at gene networks and how they interact in ways that result in human health or disease states.”
The new algorithm identified over 30 percent more associations of specific genes with biological functions than pathway-based analysis methods. More strikingly, it provided a tenfold increase in the identification of co-functioning allele pairs over pathway analysis. When represented as a network, these allele pairs form functionally interacting multi-gene modules that correspond to distinct cellular functions. The work was published in the April edition of PLoS Computational Biology. Read paper.
MIT Develops Model for Protein Interaction
Many proteins have very similar structures, yet somehow they locate and interact with only their specific partner. For years, scientists have been trying to model and design such interactions, with limited success. MIT researchers have developed a model, reported in this week’s issue of Nature, that can be used to design new protein interactions and could help scientists create proteins for use in developing new drugs.
“The proteins we design now are not likely to become drugs or therapeutics, but can be used in order to figure out the basic mechanisms of these interactions, which could be extremely valuable,” said Amy Keating, associate professor of biology and senior author of the paper being published in the April 16 issue of Nature.
Scientists who work in computational protein design, a relatively new field, try to design proteins that perform specific functions. Most of those functions involve binding to partner proteins, so one of the major challenges facing researchers is designing proteins that bind strongly to their intended target but not to other proteins with very similar structures. Read article.
MDS Analytical Technologies/AB Launch New Mass Spec
Applied Biosystems and its mass spectrometry joint-venture partner, MDS Analytical Technologies, introduced the AB SCIEX TOF/TOF™ 5800 System, the fastest, most sensitive MALDI-based mass spectrometer ever built, say the companies. More information.
University of Michigan Installs Genomatrix Platform
Genomatix reports the Informatics Core of the Center for Computational Medicine and Biology at the University of Michigan installed a Genomatix Genome Analyzer. “We are very pleased to add Genomatix advanced Next Generation Sequencing downstream analysis capabilities to our ongoing effort of providing our university-wide user base with quality tools for their data analysis", said Dr. Jim Cavalcoli, Director of the CCDU Bioinformatics Core of the Center for Computational Medicine and Biology at the University of Michigan. "We are constantly looking for tools that have both in-depth data analysis capabilities coupled to an intuitive user interface, which we found in the Genomatix Genome Analyzer. The fact that it provides command line access for our IT people was simply an added bonus.”
Physiomics Announces License Agreement with Eli Lilly
Physiomics, UK based systems biology company, signed a license agreement with Eli Lilly for a custom version of its “ModelPlayer” for in silico simulations of unspecified anticancer drugs. “We hope that the capability for Lilly scientists to directly use Physiomics’ models will strengthen the quality of the interactions within our ongoing research collaborations. This is also an important commercial and technical milestone for Physiomics as this is the first time that we have out-licensed our technology,” Dr Christophe Chassagnole, COO of Physiomics.
Lauffenburger Team Uses Fuzzy Logic to Model Cell Behavior
Living cells are bombarded with messages from the outside world -- hormones and other chemicals tell them to grow, migrate, die or do nothing... Inside the cell, complex signaling networks interpret these cues and make life-and-death decisions.
Unraveling these networks is critical to understanding human diseases, especially cancer, and to predicting how cells will react to potential treatments. Using a "fuzzy logic" approach, a team of MIT biological engineers has created a new model that reveals different and novel information about these inner cell workings than traditional computational models.
The team, led by Doug Lauffenburger, head of MIT's Department of Biological Engineering, reports its findings in the April 3 issue of the journal Public Library of Science (PLoS) Computational Biology. This is the first time that scientists have applied fuzzy logic modeling to experimental cell biochemistry data, and the approach should be applicable to any kind of cell signaling pathway, said Lauffenburger. Read article.
This article first appeared in Bio-IT World’s Predictive Biomedicine newsletter. Click here for a free subscription.