Archive for the ‘SciLit’ Category

GERV: a statis,tical method for generative evaluation of regulatory variants for transcription factor binding

Saturday, July 23rd, 2016

GERV: stats method for generative evaluation of regulatory variants
for TF binding http://bioinformatics.oxfordjournals.org/content/early/2015/11/05/bioinformatics.btv565 Predicts effect of #allelic SNPs

GERV: a statistical method for generative evaluation of regulatory ariants for transcription factor binding

> Haoyang Zeng
> Tatsunori Hashimoto
> Daniel D. Kang
> David K. Gifford

Journal Club

Saturday, July 23rd, 2016

Basset: #DeepLearning the regulatory code w/…NNs by @noncodarnia lab http://genome.cshlp.org/content/early/2016/05/03/gr.200535.115 Has score for all possible SNVs in the genome

“Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks”

Identification of type 2 diabetes subgroups through topological analysis of patient similarity | Science Translational Medicine

Saturday, July 16th, 2016

Patient records
Http://stm.sciencemag.org/content/7/311/311ra174

Construction of a genetic linkage map in man using restriction fragment length polymorphisms. – PubMed – NCBI

Friday, July 15th, 2016

http://www.ncbi.nlm.nih.gov/pubmed/6247908

A deep learning framework for modeling structural features of RNA-binding protein targets

Tuesday, July 12th, 2016

#Deeplearning framework for modeling…RBP sites
http://nar.oxfordjournals.org/content/44/4/e32 Uses topic models & determines key primary & tert. struct. features

http://nar.oxfordjournals.org/content/44/4/e32

The Ascent of Mammals – Scientific American

Monday, July 4th, 2016

The Ascent of #Mammals
http://www.scientificamerican.com/article/the-ascent-of-mammals/ Overview of their slow growth & coexistence w. dinosaurs, not just advent after KT asteroid

RNA splicing is a primary link between genetic variation and disease | Science

Monday, July 4th, 2016

Splicing is a prim. link betw…variation & disease by @JKPritch, @Y_Gilad &co http://science.sciencemag.org/content/352/6285/600.long many chrom-QTLs effect protein levels

Predicting peptide binding sites on protein surfaces by clustering chemical interactions – Yan – 2014 – Journal of Computational Chemistry – Wiley Online Library

Monday, July 4th, 2016

Predicting peptide binding sites on protein surfaces by ACCLUSTER http://onlinelibrary.wiley.com/doi/10.1002/jcc.23771/abstract #Chemical interactions out perform pure #packing

Single-Cell Co-expression Analysis Reveals Distinct Functional Modules, Co-regulation Mechanisms and Clinical Outcomes

Saturday, July 2nd, 2016

#SingleCell Coexpression…Reveals Distinct Func. Modules [v clustering bulk RNAseq]… & Clinical Outcomes [in GBM]
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004892

QT:{{”
We found that the co-expressed genes observed in single cells and bulk tumors have little overlap and show distinct characteristics. The co-expressed genes identified in bulk tumors tend to have similar biological functions, and are enriched for intrachromosomal
interactions with synchronized promoter activity. In contrast, single-cell co-expressed genes are enriched for known protein-protein interactions, and are regulated through interchromosomal interactions. “}}

Integrative analyses reveal a long noncoding RNA-mediated sponge regulatory network in prostate cancer : Nature Communications : Nature Publishing Group

Saturday, July 2nd, 2016

lncRNA-mediated sponge regulatory network in prostate cancer http://www.nature.com/ncomms/2016/160315/ncomms10982/full/ncomms10982.html Few explicitly noted #pseudogenes besides PTENP1