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Archive for the 'SciLit' Category
Network Biology Publications
July 12, 2014Reference “Quantifying reproducibility in computational biolo…”
July 11, 2014PLoS ONE, 2013 vol. 8(11) pp. e80278
Quantifying reproducibility in computational biology: the case of the tuberculosis drugome.
http://www.ncbi.nlm.nih.gov/pubmed/24312207
Garijo, D; Kinnings, S; Xie, L; Xie, L; Zhang, Y; Bourne, PE; Gil, Y
QT:{{
How easy is it to reproduce the results found in a typical computational biology paper? Either through experience or intuition the reader will already know that the answer is with difficulty or not at all. In this paper we attempt to quantify this difficulty by reproducing a previously published paper for different classes of users (ranging from users with little expertise to domain experts) and suggest ways in which the situation might be improved. Quantification is achieved by estimating the time required to reproduce each of the steps in the method described in the original paper and make them part of an explicit workflow that reproduces the original results. Reproducing the method took several months of effort, and required using new versions and new software that posed challenges to reconstructing and validating the results. The quantification leads to "reproducibility maps" that reveal that novice researchers would only be able to reproduce a few of the steps in the method, and that only expert researchers with advance knowledge of the domain would be able to reproduce the method in its entirety. ….
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.@pebourne Perhaps we need to educate biomedical data PhD students for more diverse careers #ismb #AFP14
PLOS Biology: The Ecology of Collective Behavior
July 11, 2014#Ecology of Collective Behavior
http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001805 #Network structure reflects resource patchiness, operating costs & threat of rupture
Pseudogene expression in TCGA data
July 11, 2014http://www.nature.com/ncomms/2014/140707/ncomms4963/full/ncomms4963.html
The Pan-Cancer analysis of pseudogene expression reveals biologically and clinically relevant tumour subtypes
Leng Han
Yuan Yuan
Siyuan Zheng
Yang Yang
Jun Li
Mary E. Edgerton
Lixia Diao
Yanxun Xu
Roeland G. W. Verhaak
Han Liang
Ontologies in Quantitative Biology: A Basis for Comparison, Integration, and Discovery
July 5, 2014#Ontologies in Quantitative Biology
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000374 Nice example (RTKs) showing utility of #DAGs & good normalized #bibliometrics
RTK = receptor Tyr Kinase
norm pub stats = Hits per million in pubmed
Looking for a tool to find fusion transcript — use Grep :)
June 28, 2014The “Grep” Command But Not FusionMap, FusionFinder or ChimeraScan Captures the CIC-DUX4 Fusion Gene from Whole Transcriptome Sequencing Data on a Small Round Cell Tumor with t(4;19)(q35;q13)
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0099439
amino acid changes in 1000 Genomes Project Thornton Lab
June 23, 20141000G v disease variants
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003382
A mammalian pseudogene lncRNA at the interface of inflammation and anti-inflammatory therapeutics | eLife
June 22, 2014QT:{{”
We identify an lncRNA pseudogene, Lethe (named after the mythological river of forgetfulness, for its role in negative feedback), which is expressed in response to proinflammatory cytokines TNFα and IL-1β, and the anti-inflammatory agent, dexamthasone, but is not responsive to microbial components, and is primarily found on the chromatin. Lethe is regulated by RelA, independent of pseudogene family members and proximal genes. Additionally, Lethe is dramatically downregulated in aged spleen. Finally, Lethe binds directly to RelA to inhibit NF-κB DNA binding activity. These findings suggest that Lethe may function as a novel negative regulator of NF-κB, to help fine tune the inflammatory response.
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A mammalian #pseudogene #lncRNA at the interface of inflammation… Lethe may down-regulate NF-kB via binding to RelA
http://elifesciences.org/content/2/e00762
No use of Gencode pgenes !
cancer mutation rates versus chromatin
June 14, 2014Chromatin organization is a major influence on regional mutation rates in human cancer cells
Benjamin Schuster-Böckler & Ben Lehner
http://www.nature.com/nature/journal/vaop/ncurrent/abs/nature11273.html
Bioengineering and systems biology. Ann Biomed Eng. 2006 – PubMed – NCBI
June 14, 2014Bioengineering & #systemsbiology. Classic def’n in terms of the “4 M’s”—Measurement, #Mining, Modeling & Manipulation
http://www.ncbi.nlm.nih.gov/pubmed/16474915
QT:{{”
Systems Biology can also be defined operationally, as
by the MIT Computational & Systems Biology Initiative,
in terms of the “4 M’s”—Measurement, Mining, Modeling,
and Manipulation—illustrated schematically in Fig. 1 (see
http://csbi.mit.edu/).
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