GeneGo, Bayer Schering Pharma Renew Agreement
GeneGo, a systems-biology and pathway-analysis software and database provider, announced that Bayer Schering Pharma has renewed its MetaCore licenses for another three years.
MetaCore is a software suite for pathway analysis and gene expression date mining.
GeneGo said it also in the process of building disease-specific platforms in cancer and for cardiovascular diseases, a task that includes blueprint pathway maps, processes, and mechanisms as well as offering public domain experimental data and disease ontologies.
"MetaCore is widely used in Bayer in multiple departments including bioinformatics, oncology, cardiology, and women's health for data mining and analysis of multiple omics experimental data such as gene expression and proteomics," Julie Bryant, vice president of Business Development at GeneGo, said in a statement.
Persistent Systems Becomes caBIG Support Service Provider
Persistent Systems, a provider of outsourced product-development services headquartered in India, announced it has been approved as a cancer Biomedical Informatics Grid Support Service Provider, which is a National Cancer Institute initiative with a grid infrastructure, data repositories, and interoperable software.
Companies considered compliant with caBIG’s standards for support service providers are independent of NCI but have been approved by meeting specific criteria of performance.
Persistent is now licensed as a caBIG Support Service Provider in all four support categories: help desk support; adaptation and enhancement of caBIG-compatible software applications; deployment support for caBIG software applications; and documentation and training materials and services.
Among its tasks will be caTissue support services, caBIG application development and local customizations, porting legacy non-caBIG applications to make them caBIG compatible, integration of caBIG applications with a variety of IT systems, legacy data migration, deployment, and maintenance of caBIG applications, onsite and webinar-based training, development training materials such as eLearning portals, user manuals, and guides.
The project’s caTissue suite is the tissue bank repository tool for biospecimen inventory, tracking, and annotation.
Persistent said it has contributed to seven of caBIG’s software applications and customized installations of caTissue at institutions in the US and Europe. Persistent has also delivered caBIG support services to the cancer centers involved in the Pilot Enterprise Adoption Program.
NCI to Provide $90M in Funding for Cancer Genome Atlas Centers
The National Cancer Institute has committed up to $90 million over the next five years to support between four and ten new centers to advance its Cancer Genome Atlas program.
The institute will spend as much as $18 million in 2009 for between two and four Genome Characterization Centers, and between two and six Genome Data Analysis Centers in order to roll out the next phase of the CGA program.
The main aim of the coming phase of the CGA is to provide genome-wide catalogs of genomic alterations for between 20 and 25 types of human cancer. These alterations could then be used to identify and accelerate development of new diagnostic and prognostic markers, new targets for drug interventions, and new cancer prevention and treatment strategies.
NCI sees the CGA as a “unique reference resource on cancer-specific genomic aberrations for the cancer research community at large,” according to NCI’s funding announcement.
The CGA’s Pilot Project began in 2006 through a collaboration with the National Human Genome Research Institute designed to determine the feasibility of cataloging genomic alterations associated with cancer, with a focus on glioblastoma multiforme, serous cystadenocarcinoma of the ovary, and squamous carcinoma of the lung.
That project succeeded in demonstrating that cancer-associated genes and genomic regions can be identified by combining genomic information with biological and clinical data, and that sequencing certain regions can be efficient and cost-effective, NCI explained.
The central aim for the interactive group of Genome Characterization Centers will be to use genomic and epigenomics analysis technologies for high-resolution genome-wide characterization of cancer-related alterations in the genome.
These centers will use high-throughput technologies to analyze defined sets of cancer biospecimens to be provided by the Biospecimen Core Resource. These centers will develop four types of data, including raw data, processed data, segmented data, and summary data.
The main goals for the two to six Genome Data Analysis Centers will be to develop two types of analytical pipelines. One goal is to develop and implement bioinformatics systems using available tools, quality control measures, and bioinformatics tools for high-throughput processing and analysis of genome-wide data.
The second aim is to create a “biology-centric” computational pipeline for more advanced analyses to develop models and to identify potential translational directions and outcomes from the CGA data. One type of pipeline is designed to integrate the CGA data via a high-throughput pipeline. The second pipeline will use novel algorithms, models, and other bioinformatics and computational tools to provide biologically relevant results from the CGA data.
In order to fulfill these goals there will be two types of Genome Data Analysis Centers. One will perform data integration, and another type will conduct higher levels of translational genomic analysis. All of these centers will work together to develop strategies for data management, determine the types of analysis to be performed, and optimize the mechanisms for communicating information back to those who participated in the project.
More information about the TCAG funding announcement is available here.
European Scientists Publish Detailed Plan to 'Propel' Systems Biology
A group of European scientists has published a set of recommendations for science funders and policy makers that the group said will “propel Europe to the forefront of systems biology” and help to advance personalized medicine and shorten the drug discovery and development process.
Over 110 experts participated in ten workshops to develop what the authors of the report, published by the European Science Foundation, call a “practical guide to achieving major breakthroughs in biomedical systems biology.”
The science policy briefing states that conventional biological approaches cannot unravel the complicated interactions involved in cellular functioning, and, because of that, “drug design often fails.” These authors say that their recommendations “outline the necessary steps of promoting the creation of pivotal biomedical systems biology tools and facilitating their translation into crucial therapeutic advances.”
Mathematical modeling, in particular, will be an important part of more focused and successful systems biology research, the group believes. And greater monetary investment and support of systems biology will be essential to achieving their goals.
The group describes a number of moves the European Community should take to push systems biology forward.
For example, for colorectal cancer, the group recommends initiating systems biology projects focusing on tumor-induced angiogenesis using multiscale mathematical modeling, incorporating biomechanical and fluid-dynamic effects; carrying out studies on well-characterized, highly important cancer types such as colorectal cancer to better understand treatment responses by using models that encompass multiple spatio-temporal scales and data sets; and investing further research effort in colorectal cancer modeling directed towards elucidating the interplay between the biochemical networks involved in regulating normal intestinal tissue renewal and understanding how these networks become disregulated during the early stages of carcinogenesis.
In trying to understand the relationship between aging and cancer, the group advises initiating interdisciplinary projects investigating the temporal, accumulative, and integrative aspects of the ageing process that is caused by a gradual increase of molecular and cellular damage; using mathematical models to elucidate the impact of cellular senescence on aging and malignant transformation; and exploiting systems biology approaches to investigate the effect of caloric restriction on ageing and cancer.
For inflammatory disease research, the group recommends developing multi-scale computational models of networks that control proliferation, homing, function, and survival of T lymphocytes and other inflammation-relevant cell types to predict the outcome, and create in vitro and in vivo models to unravel the dynamics of cell signaling and organization in inflammation, and how it interacts with cancer development.
The paper also details systems biology approaches for diabetes, chronobiology and chronotherapy, and nervous system disorders, and it offers recommendations concerning integrating experimental and theoretical approaches and creating dynamic models of biological processes.