lens, align.

Lang ist Die Zeit, es ereignet sich aber Das Wahre.

what we were, and what we are.

2015-02-15 14:31:16 | Science News


□ Kiwi: a tool for integration and visualization of network topology and gene-set analysis:

>> http://www.biomedcentral.com/1471-2105/15/408

The shortest path length (SPL) measures the shortest distance between two gene-sets and is a property of the network that indicates whether the two gene-sets are interacting directly or indirectly via a certain number of intermediates.






□ Computation in Dynamically Bounded Asymmetric Systems: 動的な有界非対称ネットワークの計算。制約的生体システムのエントロピーを修正

>> http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004039

very simple organizational constraints that combine these motifs can lead to spontaneous computation and so to the spontaneous modification of entropy that is characteristic of living systems.

the underlying computational elements of the network are not themselves stable. Instead, the overall boundedness of the system is provided by the asymmetrical coupling between excitatory and inhibitory elements commonly observed in neuronal and molecular networks.

Essentially, a nonlinear time-varying dynamic system will be called contracting if arbitrary initial conditions or temporary disturbances. are forgotten exponentially fast, trajectories of the perturbed system return to their unperturbed behavior w/ exponential convergence rate

A nonlinear contracting system has the following properties

・global exponential convergence and stability are guaranteed
・convergence rates can be explicitly computed as eigenvalues of well-defined Hermitian matrices
・combinations and aggregations of contracting systems are also contracting
・robustness to variations in dynamics can be easily quantified




□ Complexity Measurement Based on Information Theory and Kolmogorov Complexity:

>> http://www.mitpressjournals.org/doi/abs/10.1162/ARTL_a_00157

integrate the Shannon's information theory and Kolmogorov complexity, applied to elementary cellular automata and simulations of the self-organization of porphyrin molecules.




□ Biology How Does Information/Entropy/ Complexity fit in?

>> https://t.co/0HRIFXcq1P

The amount of compression is a good way to approximate K(s)
–Compression of Human Genome ~ 12%

Conditional Kolmogorov Complexity:
K(x|y) the shortest program which spits out xgiven y
Not Symmetric, so still need to find a good distance metric between two sequences




n0rr:
コルモゴロフ複雑性 K(X)の概算のため、Cilibrasi とVitanyi は圧縮を用いることを提案した。K(x)は文字列x の最高の圧縮と考えられるためである。 file:///Users/nor/Downloads/IPSJ-SES2011021.pdf




□ GenoMetric Query Language: A novel approach to large-scale genomic data management:

>> http://bioinformatics.oxfordjournals.org/content/early/2015/02/02/bioinformatics.btv048.short

GMQL leverages a simple model that provides abstractions of genomic region data and associated experimental, biological & clinical metadata. GenoMetric Query Language can be used independently or within GenData 2020 a server-based architecture based on Hadoop & Apache Pig platform




□ flowCL: ontology-based cell population labelling in flow cytometry

>> http://bioinformatics.oxfordjournals.org/content/early/2015/01/20/bioinformatics.btu807.short

FlowCLの論文が出てた。RとSPARQLを併用した細胞集団の意味論的標識化。

flowCL, a software package that performs semantic labelling of cell populations based on their surface markers and applied it to labelling. flowCL executes queries against the Cell Ontology, hosted on a triplestore, a database for storage and retrieval of RDF triples.




□ GRANITE – an integrative genomic tool for large complex data analysis:

静的発現データの経時評価と相互ネットワーク生成のための統合的ゲノムツール

>> http://www.rna-seqblog.com/granite-an-integrative-genomic-tool-for-complex-data-analysis/

responder AND non-responder yields the ‘common’ or ‘intersection’ network made up of the relationships that are common to both responder and non-responder groups. GRANITE supports six different methods to partition a graph using these logical operators:

GRANITE drops nodes of zero degree(spurious/no connections) in the induced subgraph. Network models are induced for both the responder group and the non-responder group, and then analysis is performed on the partitions defined above through graph visualization and graph measures.






□ Integrating Large-Scale RNA-Seq and CLIP-Seq Datasets Enables Study of lncRNA:

>> http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4294205/




□ Multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development:

>> http://www.sciencedirect.com/science/article/pii/S1350946215000063






□ Introduction to Biodiversity Informatics:

>> http://figshare.com/articles/Introduction_to_Biodiversity_Informatics/1295382

Current taxonomic data

• 15-20k new spp. described annually (2M total)
• 30k nomenclatural acts (12M total)
• 20k phylogenies (750k total)
• 31k taxa sequenced (360k taxa total)
• 800k BioMed papers (40M total pp. of taxonomy)


□ ontology usage:








□ SynBioLGDB: A Gateway for Logical Biology: a resource for experimentally validated logic gates in synthetic biology:

>> http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308699/

生物学的論理ゲートの概念。AND, OR, NOR, NOT, NAND, XOR,を含む189のロジックゲートを有し、バイナリでないので、アナロジーの複雑さを軽減できる他、リボザイムベースのNORゲート問題に有用なリソースとなる。

SynBioLGDB has 80 AND gates, 8 Buffer gates, 7 Combinatorial gates, 10 NAND, 16 NOR, 28 NOT, 17 OR gates, 7 XOR gates and 16 other gates. diverse genetic logic gates capable of generating a Boolean function play critically important roles in synthetic biology. Basic genetic logic gates have been designed to combine biological science with digital logic.




□ GBIF, biodiversity informatics and the "platform rant":

>> http://iphylo.blogspot.jp/2015/01/gbif-biodiversity-informatics-and-rant.html

"the goal of the platform is NOT to "help" users - that simply reinforces the distinction between you and the "users""




□ LFQC: a lossless compression algorithm for FASTQ files: better than gzip, bzip2, fastqz, fqzcomp, G-SQZ, SCALCE, DSRC

>> http://bioinformatics.oxfordjournals.org/content/early/2015/01/20/bioinformatics.btu701.short

The improvement obtained is up to 225% on the datasets (SRR065390_1), the average improvement (over all the algorithms compared) is 74.62%




□ Machine Learning for Bioinformatics: MATLAB:

>> http://au.mathworks.com/examples/bioinfo/category/machine-learning-for-

Identifying Biomolecular Subgroups Using Attractor Metagenes Algorithm which are defined as the attracting fixed points of iterative process. The algorithm exists within the broad family of unsupervised machine learning. Related algorithms include principal component analysis, various clustering algorithms (especially fuzzy c-means), non-negative matrix factorization, and others.




□ Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables:

>> http://scitation.aip.org/content/aip/journal/jcp/139/21/10.1063/1.4830403

a machine learning method of SandCV provides a description of the system that closely mimics one based on the conventional dihedral angles. This system is a benchmark for free energy calculations and has well-known and highly nonlinear collective variables.




□ New Computational Framework Provides Pipelines for Reproducible Multi-Omics Data Analysis:

>> https://www.genomeweb.com/informatics/new-computational-framework-provides-pipelines-reproducible-multi-omics-data-analysis



□ BioGPS Featured Article- Multi-omic landscape of rheumatoid arthritis: re-evaluation of drug adverse effects:

>> http://sulab.org/2015/02/biogps-featured-article-multi-omic-landscape-of-rheumatoid-arthritis-re-evaluation-of-drug-adverse-effects/





□ A Memory Efficient Short Read De Novo Assembly Algorithm:

>> https://www.jstage.jst.go.jp/article/ipsjtbio/8/0/8_2/_pdf

The average maximum memory consumption of the proposed method for human chromosome 14 was approximately 54% of SOAPdenovo2 and that was approximately 63% of Velvet. the vertices that are put together in a path are as- signed the same label. A path from the start vertex to the end vertex represents a subgraph. Multiple subgraphs are created in this process.




□ PLNseq: a multivariate Poisson lognormal distribution for high-throughput matched RNA-sequencing read count data

>> http://onlinelibrary.wiley.com/doi/10.1002/sim.6449/abstract

The correlation is directly modeled through Gaussian random effects, and inferences are made by likelihood methods. A three-stage numerical algorithm is developed to estimate unknown parameters and conduct differential expression analysis.

Results using simulated data demonstrate the method performs reasonably well in terms of parameter estimation, DE analysis power, robustness. PLNseq also has better control of FDRs than the benchmarks edgeR and DESeq2.




□ Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species:

>> http://biorxiv.org/content/biorxiv/early/2015/02/06/014902.full.pdf




□ EMASE: Expectation-Maximization algorithm for Allele Specific Expression:

>> https://pypi.python.org/pypi/emase/0.9.0

The EM algorithm employed in EMASE models multi-reads at the level of gene, isoform, and allele and apportions them probabilistically.

emase.Sparse3DMatrix

class emase.Sparse3DMatrix.Sparse3DMatrix(other=None, h5file=None, datanode='/', shape=None, dtype=<type 'float'>)




□ Empirical GO: Measure Enrichment using an Empirical Sampling Approach

>> http://sgjlab.org/empirical-go/

The Empirical GO generates the empirical distribution of the number of mRNA target genes in GO terms and returns p-values for enrichment. The code accompanies a manuscript submitted for publication in Bioinformatics.




□ Parallel de Bruijn Graph Construction and Traversal for de novo Genome Assembly:

>> http://www.homolog.us/blogs/blog/2015/01/27/parallel-de-bruijn-graph-construction-and-traversal-for-de-novo-genome-assembly/

a novel algorithm that leverages 1-sided communication capabilities of Unified Parallel C to facilitate the requisite fine-grained parallelism. and avoidance of data hazards, while analytically proving its scalability properties.




□ Parallel Bayesian Network Structure Learning for Genome-Scale Gene Networks:

>> http://ieeexplore.ieee.org/xpl/login.jsp




OneCodex:
generate + share public links for your NGS data analyses on One Codex http://blog.onecodex.com/2015/02/03/better-data-sharing/




□ Orion: Scaling Genomic Sequence Matching with Fine-Grained Parallelization:

>> http://ieeexplore.ieee.org/xpl/login.jsp

a fine-grained parallelism technique called Orion, that divides the input query into an adaptive number of fragments and shards the database.

higher parallelism (and hence speedup) and load balancing than database sharding alone, while maintaining 100% accuracy. 12.3X faster than mpiBLAST for solving a relevant comparative genomics problem.




□ Natera Adopts the DNAnexus Cloud Genomics Platform to Support a Portfolio of Next-Generation Genetic Tests:

>> http://www.businesswire.com/news/home/20150127005167/en/Natera-Adopts-DNAnexus-Cloud-Genomics-Platform-Support




□ RSEM-EVAL – for evaluating assemblies when the ground truth is unknown:

>> http://www.rna-seqblog.com/rsem-eval-for-evaluating-assemblies-when-the-ground-truth-is-unknown/

去年の6月にbiorxivから発表されたDETONATEに関する論文がリリース。

"REF-EVALおよびRSEM-EVALが示唆するアセンブリの相対精度において、TrinityはコンティグとヌクレオチドレベルのF1とKC Scoreに関して最も正確なアセンブリを生成する。"




□ Lauded New Orleans biotech firm Renaissance Rx facing financial trouble: 遺伝子検査株高騰の反動が早くも顕在化してる模様

>> http://www.nola.com/business/index.ssf/2015/02/lauded_new_orleans_biotech_fir.html




□ RainDance, U Chicago Sue 10X Genomics for Patent Infringement:

>> https://www.genomeweb.com/business-news/raindance-u-chicago-sue-10x-genomics-patent-infringement

long-readの先進的技術が注目されてた10xに特許侵害の訴訟。AGBTでの詳報を目前にして。。

10x leverages existing short-read NGS but fills in knowledge gaps by taking a DNA/ partitioning the molecules in a massively parallel manner. Each partition has its own barcode, and once the partitioning is completed, the fragments are then pieced together into a long read.

「基板上のトランスポートで発生する反応」が訴状なら、NGSの大部分に引っかかるような気がするけど、"microfabricated"の仕様次第かも。10xの革新性はDNAサンプルの分子の大規模系列的なパーティションで、JP Morgan会議での発表時に5550万ドルを調達してる。




□ Orion Genomics LLC - Product Pipeline Analysis, 2014 Update, Has Been Published: New Market Study:

> http://www.releasewire.com/press-releases/new-market-study-orion-genomics-llc-product-pipeline-analysis-2014-update-has-been-published-577018.htm




□ GrammR: Graphical Representation & Modeling of Count Data Application in Metagenomics: metric multidimension scaling

>> http://bioinformatics.oxfordjournals.org/content/early/2015/01/19/bioinformatics.btv032.abstract

a novel procedure for determining the number of clusters in conjunction with PAM (mPAM). using metric multidimensional scaling (MDS) as an alternative to PCoA for graphical representation.




□ BioGraphServ: Bioinformatics Graph Server

>> http://biographserv.com/bgs/view_project/bf757a08ccf54eae9d3ba37990bc8d61/

BGS using the Django framework, Graphs/Analysis use Pandas/Matplotlib. dispatched to asynchronous workers (Celery) & call a reference server

Drug & Dropで使用できるバイオインフォマティクス用グラフ・サーバ。BED, VCF, Expression, CuffDiffで自動解析。




c_z:
“Graph Analysis and Visualization: Discovering Business Opportunity in Linked Data” http://www.wiley.com/WileyCDA/WileyTitle/productCd-1118845846.html





□ Advantages of distributed & parallel algorithms: leverage Cloud Computing platforms for large-scale genome assembly:

>> http://f1000research.com/articles/4-20/v1

the Hadoop implementation of the Contrail algorithm in the Map phase scans each read and emits the key-value pairs (u, v) corresponding to overlapping k-mer pairs that form an edge. by aggregation of identical K-mers in the Reduce phase, where also linear paths of the de Bruijn graph are calculated and continuously overlapping K-mers are simplified into single graph nodes representing longer stretches of sequence.




□ Graphical Fragment Assembly format

>> http://lh3.github.io/2014/07/19/a-proposal-of-the-grapical-fragment-assembly-format/

例の開発中だったゲノムアセンブリの新フォーマット、ABySSにネイティブサポートされた模様。




□ The bioboxes RFC: Request for comments on interchangeable bioinformatics containers

>> https://github.com/bioboxes/rfc




□ GenomicScape: a free online data-mining platform to quickly identify molecular changes during any biological process:

>> http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004077




□ BASIL and ANISE: Methods for the Detection and Assembly of Novel Sequence in High-Throughput Sequencing Data

>> http://bioinformatics.oxfordjournals.org/content/early/2015/02/01/bioinformatics.btv051.short

approaches for detecting insertion breakpoints and targeted assembly of large insertions from non-mapping HTS paired data.




sgwrhdk:
創薬等PF最先端セミナーにて、構造生命科学データクラウドVaProS(VAriation effect on PROtein Structure and function) を披露目 http://p4d-info.nig.ac.jp/vapros/




□ Ramsey theory for infinite words: extensions of infinite theorem/Hindman's finite sums theorem/MillikenTaylor theorem

>> http://www.liafa.jussieu.fr/web9/manifsem/description_en.php?idcongres=1798




AIP_Publishing:
Global solar irradiation prediction using a multi-gene genetic programming approach http://ow.ly/IBKT1

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