Archive for the 'SciLit' Category
Recent Explosive Human Population Growth Has Resulted in an Excess of Rare Genetic Variants
September 23, 2012paper/talk on software networks
September 23, 2012From C Myers:
Some links to a paper examining the structure of software networks and their connection to biological networks. “Much of the software design involved object-oriented programming (with networks describing interactions among classes, rather than among functions as in procedural call graphs);” Thus, perhaps some of the conclusions are specific to OOP.
Ordered Cyclic Motifs Contributes to Dynamic Stability in Biological and Engineered Networks. Proceedings of the National Academy of Sciences (2008)
September 15, 2012Summary adapted from from Koon-Kiu (KKY):
This paper studied cyclic motifs (cycles) in biological and
technological networks. A cycle can be characterized by the number of clockwise and counter-clockwise links, the number of pass-through nodes and the number of sources/sinks, etc. Direct counting of cycles of various length suggests a dependence between neighboring links, and such dependence is modeled by an interacting spin model. Fitting to the spin model shows that neighboring links tend to be in opposite directions (antiferromagnetic), resulting in a depletion of feedback loops in networks. Stability analysis concluded that the lack of feedback loop stabilizes the system in terms of perturbation around the fixed point.
Ma’ayan A, Cecchi GA, Wagner J, Rao AR, Iyengar R, Stolovitzky G. Ordered Cyclic Motifs Contributes to Dynamic Stability in Biological and Engineered Networks. Proceedings of the National Academy of Sciences 105, 19235-40 (2008) PMID: 19033453
http://ukpmc.ac.uk/abstract/MED/19033453/reload=0;jsessionid=aeku6lFJSKlT8wnr9czW.12
Cell – Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing
September 14, 2012http://www.cell.com/abstract/S0092-8674%2812%2901061-6?utm_source=ECE001&utm_campaign=&utm_content=&utm_medium=email&bid=OV63V3F:KK4SNSD 23 whole genome tumor/normal pairs
This was covered in NYT a few days ago
http://www.nytimes.com/2012/09/10/health/research/for-a-lung-cancer-drug-treatment-may-be-within-reach.html No direct access to ‘vcf’ files.
Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes. PLoS Computational Biology. 7, e1002319 (2011)
September 14, 2012Summary adapted from Declan (DC):
The authors attempt to devise a few simple statistical metrics using high-throughput experimental data (many experiments involving immuno-precipitation coupled with mass spec) in order to predict protein-protein and domain-domain interactions involved in
transcription-related complexes. Each experiment entails using mass spec in order to identify the “prey” proteins that associate with a given “bait” protein. Broadly, protein-protein interactions between such prey proteins are predicted with statistical metrics that assign a likely interaction between a pair of proteins if that pair consistently co-occurs (in high abundance) across multiple
experiments. An example of one of their well-performing metrics is the Sorenson coefficient, which is the ratio of twice the number of experiments in which both proteins occur to the number of experiments in which either or both of these proteins occur (naively, this can be thought of as the degree of intersection between the experiments in which Protein A occurs and the experiments in which Protein B occurs). Using the top 10% of predicted interactions for each of their 4 statistical metrics, they validate many interactions with data from the literature, and they also perform experimental validation and docking studies in order to validate a tiny number of their
predictions. They supply their resultant networks as web-accessible data files.
Mazloom AR et al.
Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes. PLoS Computational Biology. 7, e1002319 (2011) PMID: 22219718
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002319
Cell – Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing
September 14, 2012http://www.cell.com/abstract/S0092-8674%2812%2901061-6?utm_source=ECE001&utm_campaign=&utm_content=&utm_medium=email&bid=OV63V3F:KK4SNSD 23 whole genome tumor/normal pairs
Cell – Genomic Landscape of Non-Small Cell Lung Cancer in Smokers and Never-Smokers
September 14, 2012Increased number of microRNA target sites in genes encoded in CNV regions. Εvidence for an evolutionary ge nomic interaction?
September 9, 2012http://www.ncbi.nlm.nih.gov/pubmed/21441354
QT:”
By performing in silico whole genome analysis, we demonstrate that both the number of miRNAs that target genes found in CNV regions as well as the number of miRNA-binding sites are significantly higher than those of genes found in non-CNVregions.
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CiteSeerX — Tutorial on Phylogenetic Tree Estimation
September 4, 2012Kim & Warnow (1999)
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.3455
Mutational Signatures of De-Differentiation in Functional Non-Coding Regions of Melanoma Genomes
August 25, 2012http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1002871 QT:”
To understand the functional impact of non-coding somatic variation, we leveraged functional data generated by the ENCODE Project Consortium. We analyzed regulatory regions derived from multiple different cell types and found that melanocyte-specific regions are among the most depleted for somatic mutation accumulation.
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linkstream2 microblog 