San Diego, CA, USA. In a significant leap forward in the understanding the development of specific tissue types in mammals, an international team of scientists succeeded in mapping the entire network of DNA-binding transcription factors and their interactions. This global network, indicating which factors can combine to determine cell fate, appears in the journal Cell.

Transcription factors (TFs) are proteins that bind to specific DNA sequences in order to direct which genes should be turned on or off in a tissue. Tissue specificity (e.g. whether embryonic tissue develops into lungs or kidneys or skin) is determined by how and which TFs bind to genes.

Between 2,000 and 3,000 transcription factor proteins are encoded by the human genome, potentially creating more than 4 million potential protein pairings.

Stanford, CA, USA. Human blood is a trove of biological information, now accessible by a software algorithm that enables a common laboratory device to virtually separate a whole-blood sample into its different cell types.

This development has a near-term potential for adding a powerful tool to the toolset for biological investigations. The algorithm enables detection of medically important gene-activity changes that are specific to any one of the cell types present in the blood sample. The authors believe that uses of the new algorithm may allow doctors to better identify the onset of genetic disorders, cancers, and a variety of other problems.

In a study that appears Nature Methods, the scientists reported that they had successfully used the new technique to pinpoint changes in one cell type that flagged the likelihood of kidney-transplant recipients rejecting their new organs. Without the software, these gene-activity flags would have gone unnoticed.

Blacksburg, VA, USA. Significant advances in modeling biological processes in recent years are due in large measure to successful deployment of the Systems Biology Markup Language (SBML). The tool is suitable for models of metabolism, cell signaling, and other processes.

SBML supports exchange of quantitative models of biochemical networks between different computer systems, allowing model sharing and publication in a form other researchers can use in their own environments. The initial paper has exceeded 500 citations in the ISI Web of Knowledge, a database that documents the impact of scientific publications. [C1]

The Systems Biology Graphical Notation (SBGN), described in a previous TS-Si.org article, provided a set of standards for graphically representing biological information — the biology equivalent of a circuit diagram in electronics. [C2] The potential convergence with SBML has already demonstrated powerful results and offers the basis for extensions into new realms of research.

Champaign, IL, USA. With the world awash in information, curating all the scientifically relevant bits and bytes is an important task, especially given digital data’s increasing importance as the raw materials for new scientific discoveries, an expert in information science at the University of Illinois.

Data curation is the active and ongoing management of data interesting to science throughout their lifecycle. Carole L. Palmer, a professor of library and information science at the University of Illinois, says that scientific data curation has come into irs own and is now understood to be an important part of supporting and advancing research.

“There’s a lot of recognition now of the value of data as assets to institutions and to the scientific enterprise, more generally,” Palmer said. “Saving only the publications that report the results of research simply isn’t enough anymore. Researchers also need access to data that can be integrated and re-used in new ways. This is especially important in data-intensive science, where the power of discovery lies in applying computational approaches to large, aggregated data sets.”

San Francisco, CA, USA. Governments rightly request the advice of scientists on matters of fact that affect the public good, from climate change to cancer screening. Scientists must then assess available data and present recommendations based on the data. But what is the role of scientists when politicians see these recommendations as inconvenient?

In mid-November 2009 the United States Preventive Services Task Force (USPSTF), which reviews scientific evidence to develop recommendations for the US health care community, revised their recommendations to say that women need not generally begin mammographic screening for breast cancer until age 50 [N1].

This revision, which brings the Task Force's recommendations closer to those of the WHO, the UK, and the American College of Physicians, touched off a political firestorm in the US. The new recommendations amounted to a change in the evidence-based rating on screening women between ages 40 and 50 from grade B (recommended as likely to be of moderate benefit) to grade C (recommended against as a routine service, as net benefit is likely to be small, although there may be considerations that support providing the service in an individual patient).