Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1093/bioinformatics/btu284 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btu284 C4058927!4058927 !24932008     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\24932008 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Bioinformatics 2014 ; 30 (12 ): i78-86 Nephropedia Template TP {{tp|p=24932008 |t=2014. A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data |pdf=|usr=}}{{24932008 }} gab.com Text A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24932008 #FOAvip MOTIVATION: High-throughput sequencing of tumor samples has shown that most tumors exhibit extensive intra-tumor heterogeneity, with multiple subpopulations of tumor cells containing different somatic mutations. Recent studies have quantified this intra-tumor heterogeneity by clustering mutations into subpopulations according to the observed counts of DNA sequencing reads containing the variant allele. However, these clustering approaches do not consider that the population frequencies of different tumor subpopulations are correlated by their shared ancestry in the same population of cells. RESULTS: We introduce the binary tree partition (BTP), a novel combinatorial formulation of the problem of constructing the subpopulations of tumor cells from the variant allele frequencies of somatic mutations. We show that finding a BTP is an NP-complete problem; derive an approximation algorithm for an optimization version of the problem; and present a recursive algorithm to find a BTP with errors in the input. We show that the resulting algorithm outperforms existing clustering approaches on simulated and real sequencing data. AVAILABILITY AND IMPLEMENTATION: Python and MATLAB implementations of our method are available at http://compbio.cs.brown.edu/software/ . Twit Text FOAVip A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24932008 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24932008 #FOAvip English Wikipedia <ref>{{Cite pmid|24932008 }}</ref> A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data #MMPMID24932008 Hajirasouliha I ; Mahmoody A ; Raphael BJ Bioinformatics 2014[Jun]; 30 (12 ): i78-86 PMID24932008 show ga MOTIVATION: High-throughput sequencing of tumor samples has shown that most tumors exhibit extensive intra-tumor heterogeneity, with multiple subpopulations of tumor cells containing different somatic mutations. Recent studies have quantified this intra-tumor heterogeneity by clustering mutations into subpopulations according to the observed counts of DNA sequencing reads containing the variant allele. However, these clustering approaches do not consider that the population frequencies of different tumor subpopulations are correlated by their shared ancestry in the same population of cells. RESULTS: We introduce the binary tree partition (BTP), a novel combinatorial formulation of the problem of constructing the subpopulations of tumor cells from the variant allele frequencies of somatic mutations. We show that finding a BTP is an NP-complete problem; derive an approximation algorithm for an optimization version of the problem; and present a recursive algorithm to find a BTP with errors in the input. We show that the resulting algorithm outperforms existing clustering approaches on simulated and real sequencing data. AVAILABILITY AND IMPLEMENTATION: Python and MATLAB implementations of our method are available at http://compbio.cs.brown.edu/software/ . |*Algorithms [MESH] |*High-Throughput Nucleotide Sequencing [MESH] |*Sequence Analysis, DNA [MESH] |Cluster Analysis [MESH] |Gene Frequency [MESH] |Humans [MESH] |Leukemia, Myeloid, Acute/genetics [MESH] |Mutation [MESH]A combinatorial approach for analyzing intra-tumor heterogeneity from (epmc).pdf DeepDyve Pubget Overpricing