□ RNA-seq Flux simulator: Modelling & Simulating generic RNA-Seq:
>> http://flux.sammeth.net/simulator.html
>> http://nar.oxfordjournals.org/content/early/2012/09/07/nar.gks666.full
Our models are implemented in a computer simulation pipeline called the Flux Simulator, and we show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. We further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies
RNA加水分解の断片化予測分布パラメータによる解析モジュール。複数シーケンシング・プラットフォームに適用可能
□ The ENCODE project: lessons for scientific publication
>> http://www.genomesunzipped.org/2012/09/the-encode-project-lessons-for-scientific-publication.php
>> http://www.nature.com/encode/#/threads/characterization-of-intergenic-regions-and-gene-definition
The ENCODE Project has this week released the results of its massive foray into exploring the function of the non-protein-coding regions of the human genome. This is a tremendous scientific achievement, and is receiving plenty of well-deserved press coverage; for particularly thorough summaries see Ed Yong’s excellent post at Discover and Brendan Maher at Nature.
□ What’s next for ENCODE?
>> http://www.nature.com/news/encode-the-human-encyclopaedia-1.11312
□ Nature Encode (iPad app)
>> http://itun.es/i6DT65k
Nature EncodeのiPad app、帰宅して弄り倒してるけど面白い。記事の関連性や、研究の体系が直感的に連関した構成で読み応えある。でもinfographic系は苦手w
□ emblebi:
I liked a @YouTube video http://youtu.be/KiwXtHRfBC8?a ENCODE: Encyclopedia of DNA Elements
Ewan Birney of EMBL-EBI, Tim Hubbard of the Wellcome Trust Sanger Institute and Roderic Guigo of CRG talk about ENCODE, an international project which revealed that much of what has been called 'junk DNA' in the human genome is actually a massive control panel with millions of switches regulating the activity of our genes.
□ ENCODE計画: ヒトゲノムのガイドブック: ENCODE計画の成果を印刷版とオンラインで紹介
>> http://www.natureasia.com/ja-jp/nature/highlights/38750
ENCODE（Encyclopedia of DNA Elements；DNAエレメントの百科事典）計画は、ヒトゲノム中にコードされているすべての機能エレメントについて記述することを目的とするものである。ENCODEが開始されてから9年が経ち、その主な成果は今回30本の共同研究論文として発表されて、計画は完結した。
□ appistry:
ENCODE project global collaboration that wrangled more than 15 TB of genetic data from 32 labs globally http://goo.gl/frKcx #bigdata
Big data and DNA: What business can learn from junk genes
□ GENCODE: The reference human genome annotation for The ENCODE Project http://genome.cshlp.org/content/22/9/1760.full
□ genomeresearch:
ENCODE data integration on a massive scale requires new methods and guidelines http://genome.org
□ http://itunes.apple.com/app/id553487333 RT @elisadonnard: Downloaded the ENCODE App! :)
□ mark_g_vero:
http://www.nature.com/news/encode-the-human-encyclopaedia-1.11312 … ENCODE phase has come to a close, signalled by publication of 30 papers, in Nature, Genome Research...
□ simplystats:
The discussions generated by #ENCODE motivated this: Top down versus bottom up science: data analysis edition http://tmblr.co/ZFlMwwSxoN3i
□ genomeresearch:
ChIP-seq #ENCODE style http://tinyurl.com/d9duuwq
Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.
□ dnanexus:
Full ENCODE article on @genomeresearch: Revealing remarkable chromatin diversity @ regulatory elements. http://genome.cshlp.org/content/22/9/1735.full
Ubiquitous heterogeneity and asymmetry of the chromatin environment at regulatory elements
□ cshperspectives:
Should we re-define the gene? http://bit.ly/OXMxTs http://bit.ly/Q0HovP #ENCODE
□ ewanbirney:
Good Economist write up on #ENCODE. http://www.economist.com/node/21562186
A long-term effort to catalogue all the bits of the human genome that do something has released its results
□ WSJJapan:
「ヒトゲノムのほぼ80％の領域に生化学的機能があるとの発見」――。複雑な連関もあるようで、遺伝子研究がワンステップ上がった印象です。（YS）→遺伝子の砂漠、活動に満ちていた－プロジェクトで判明 http://on.wsj.com/ORyxKI
□ dgmacarthur:
Fantastic post by Sean Eddy on what ENCODE's results actually mean: http://selab.janelia.org/people/eddys/blog/?p=683 …
□ Spark for ENCODE data: A navigational paradigm for genomic data exploration:
>> http://genome.cshlp.org/content/early/2012/09/07/gr.140665.112.abstract …
□ De novo automated design of small RNA circuits for engineering synthetic riboregulation in living cells : http://m.pnas.org/content/early/2012/08/31/1203831109.full.pdf …
□ RNA-seq Coverage Effects on Biological Pathways and GO Tag Clouds
>> http://www.aporc.org/ISB/2012/Proceedings/Papers/ISB2012F41.pdf
Two functional annotation methods for clustered gene groups including biological pathways and GO terms were employed in this study. A biological pathway is one of the most meaningful clustering representations for biological function analysis.
Another functional annotation method often applied to describe gene products is Gene Ontology (GO). The GO is a set of structured vocabularies defined by Gene Ontology Consortium [10], which is aimed to provide a universal standard of functional annotation for gene products.
複数データセットでの差動発現解析の為の生物学的経路と遺伝子オントロジー・アノテーションの統合ワークフロー。
生物学的経路(KEGG)と遺伝子オントロジー(GO)を含むクラスタ化された2つの機能アノテーション・メソッド。RNA-seqのカバレッジ情報を統合し、シーケンシング時点のDEG発現及び変異株のダイナミック・ステータスを明示。従来は見落とされていた分析リソースにもアプローチする
そういえばMEDALSにもKaPPA-View4という代謝経路データベースがあり（略
バイオインフォマティクスにおいても、オミクスデータ由来の自動化された"hypothesis bulider"みたいなコミュニティベースの共有型プラットフォームを実現する場合、複数データセットのカバレッジ・アノテーションの統合・評価メソッドはもっと重要になっていくのだろうな。
□ neilfws:
Prokaryotes do it too: CRISPR, an RNA-based adaptive immune system in UniProt release 2012_08 http://bit.ly/NdkUaw
The new Genomics Laboratory is a central hub for global molecular DNA work for all Hendrix Genetics divisions, and is already producing new innovations in breeding.
Blood and tissue samples are taken from the pig, poultry and aquaculture divisions, and also from customers' stocks. Samples are then transported to the laboratory, where DNA is extracted and stored in a BioBank.
After in-house analysis and genotyping, geneticists use these to develop breeding programmes.
□ CBrowse: a SAM/BAM-based contig browser for transcriptome assembly visualization and analysis: AJAX-based web browser http://bioinformatics.oxfordjournals.org/content/28/18/2382.short?rss=1 …
□ Genomicswatch:
Hendrix launches new genomics centre - FarmersWeekly http://bit.ly/Qth4tJ
□ pathogenomenick:
Assemblage: tools for working with 2nd-gen assemblies, fasta, etc. https://github.com/sujaikumar/assemblage
□ Fluctuation tolerant read scheme for ultrafast DNA sequencing with nanopore device: ナノポアデバイスの回路スキーマ。従来のDNAシーケンサより6桁速い。 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6271754
□ BIoHAckathon 2012.
□ HyQue Architecture:
>> http://semanticscience.org/projects/hyque/index.html
evaluating scientific hypotheses about molecular event in the context of the galactose gene network
□ dbcls:
Michel Dumontier Knowledge Discovery using an Integrated Semantic Web ( #BH12 live at http://ustre.am/C6Wz )
□ dbcls:
The BioHackathon2012 symposium will start at 9:30 JST ( #BH12 live at http://ustre.am/C6Wz )
□ EnvO:
>> http://environmentontology.org/
A community Ontology tool for semantically controlled environmental description. annotation of any organism or biological samles...
□ BioInterchange: automatically creates RDF from TSV, XML etc…: Ruby code for generating RDF, potentially from GTF/GFF http://www.biointerchange.org
□ jervenbolleman:
#BH12 my slides of real complex #SPARQL queries in #bio using multiple datasources using SERVICE keyword @slideshare http://www.slideshare.net/jervenbolleman/uni-protsparqlcloud
□ fstrozzi:
#BH12 G-project speech recognition + AI engine.Talk to your computer to query biological semweb databases.Outstanding! https://github.com/dbcls/bh12/wiki/G-language-project …
□ mbeisen:
outstanding clinical dissection of ENCODE claims by @TRyanGregory http://www.genomicron.evolverzone.com/2012/09/encode-2012-vs-comings-1972/ ”ENCODE (2012) vs. Comings (1972)."
□ TheICF:
Free review article from Forestry: Boreal forest soil carbon: distribution, function and modelling http://forestry.oxfordjournals.org/content/85/2/161.full?sid=5a9df926-f6d7-4f97-9779-ffb8980e0be6 … @OxfordJournals
In this review, we address these issues through a discussion of the size and character of boreal forest soil C pool, its role in ecosystem function, the potential impacts of climate change on soil C, efforts to model these processes and the role of soil C in boreal resilience to the impacts of climate change. Soil C is fundamental to ecosystem function in terms of improving soil physical properties, increasing soil biotic activity and enhancing insulation all of which improve site productivity.
□ GASiC: Genome Abundance Similarity Correction:
>> http://sourceforge.net/projects/gasic/
>> http://nar.oxfordjournals.org/content/early/2012/08/30/nar.gks803.full
Genome Abundance Similarity Correction (GASiC), a method to estimate true genome abundances via read alignment by considering reference genome similarities in a non-negative LASSO approach. We demonstrate GASiC’s superior performance over existing methods on simulated benchmark data as well as on real data. In addition, we present applications to datasets of both bacterial DNA and viral RNA source. We further discuss our approach as an alternative to PCR-based DNA quantification.
メタゲノム資源量推定と生物種レベル診断テスト、非負値Lassoアプローチによる参照ゲノム配列の類似性を考慮したアラインメントから存在量を推定
□ An automated framework for hypotheses generation using literature:
>> http://www.biodatamining.org/content/pdf/1756-0381-5-13.pdf
The proposed HGF shares similar end goals like the SWAN but are more holistic in nature and was designed and implemented using scalable and efficient computational models of disease-disease interaction. The integration of mapping ontologies with latent semantic analysis is critical in capturing domain specific direct and indirect “crisp” associations, and making assertions about entities (such as disease X is associated with a set of factors Z).
文献ベース仮説生成自動化フレームワーク。潜在意味解析とマッピングオントロジー統合。疾患相互作用の計算設計
□ Isis Pharm. Demonstrates The Potential Of Single-Stranded RNA-Like Antisense Technology To Activate The RNAi Pathway:
>> http://ir.isispharm.com/phoenix.zhtml?c=222170&p=irol-newsArticle&ID=1730310
>> http://www.sciencedirect.com/science/article/pii/S0092867412010094
Isis Pharmaceuticals, Inc. (NASDAQ: ISIS) announced today the publication of two papers in the journal Cell demonstrating that single-stranded short interfering RNA (ss-siRNA) molecules distributed broadly, activated the RNA interference (RNAi) pathway and reduced