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Algorithms for computational biology...
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InternationalConference on Algorithms for Computational Biology (2019 :)
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Algorithms for computational biology = 6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28-30, 2019 : proceedings /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Algorithms for computational biology/ edited by Ian Holmes, Carlos Martin-Vide, Miguel A. Vega-Rodriguez.
其他題名:
6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28-30, 2019 : proceedings /
其他題名:
AlCoB 2019
其他作者:
Holmes, Ian.
團體作者:
InternationalConference on Algorithms for Computational Biology
出版者:
Cham :Springer International Publishing : : 2019.,
面頁冊數:
xvi, 225 p. :ill., digital ;24 cm.
內容註:
Invited Talk -- New Divide-and-Conquer Techniques for Large-Scale Phylogenetic Estimation -- Biological Networks and Graph Algorithms -- New Polynomial-Time Algorithm around the Scaffolding Problem -- Enumerating Dominant Pathways in Biological Networks by Information Flow Analysis -- Comparing Different Graphlet Measures for Evaluating Network Model Fits to BioGRID PPI Networks -- Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots -- PathRacer: Racing Profile HMM Paths on Assembly Graph -- Genome Rearrangement, Assembly and Classification -- A Uniform Theory of Adequate Subgraphs for the Genome Median, Halving, and Aliquoting Problems -- Lightweight Metagenomic Classification via eBWT -- MULKSG: MULtiple K Simultaneous Graph Assembly -- Counting Sorting Scenarios and Intermediate Genomes for the Rank Distance -- Generalizations of the Genomic Rank Distance to Indels -- Sequence Analysis, Phylogenetics and Other Biological Processes -- Using INC within Divide-and-Conquer Phylogeny Estimation -- Predicting Methylation from Sequence and Gene Expression Using Deep Learning with Attention -- A Mathematical Model for Enhancer Activation Kinetics During Cell Differentiation -- Transcript Abundance Estimation and the Laminar Packing Problem -- Efficient Algorithms for Finding Edit-Distance Based Motifs.
Contained By:
Springer Nature eBook
標題:
Computational biology - Congresses. -
電子資源:
https://doi.org/10.1007/978-3-030-18174-1
ISBN:
9783030181741
Algorithms for computational biology = 6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28-30, 2019 : proceedings /
Algorithms for computational biology
6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28-30, 2019 : proceedings /[electronic resource] :AlCoB 2019edited by Ian Holmes, Carlos Martin-Vide, Miguel A. Vega-Rodriguez. - Cham :Springer International Publishing :2019. - xvi, 225 p. :ill., digital ;24 cm. - Lecture notes in computer science,114880302-9743 ;. - Lecture notes in computer science ;11488..
Invited Talk -- New Divide-and-Conquer Techniques for Large-Scale Phylogenetic Estimation -- Biological Networks and Graph Algorithms -- New Polynomial-Time Algorithm around the Scaffolding Problem -- Enumerating Dominant Pathways in Biological Networks by Information Flow Analysis -- Comparing Different Graphlet Measures for Evaluating Network Model Fits to BioGRID PPI Networks -- Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots -- PathRacer: Racing Profile HMM Paths on Assembly Graph -- Genome Rearrangement, Assembly and Classification -- A Uniform Theory of Adequate Subgraphs for the Genome Median, Halving, and Aliquoting Problems -- Lightweight Metagenomic Classification via eBWT -- MULKSG: MULtiple K Simultaneous Graph Assembly -- Counting Sorting Scenarios and Intermediate Genomes for the Rank Distance -- Generalizations of the Genomic Rank Distance to Indels -- Sequence Analysis, Phylogenetics and Other Biological Processes -- Using INC within Divide-and-Conquer Phylogeny Estimation -- Predicting Methylation from Sequence and Gene Expression Using Deep Learning with Attention -- A Mathematical Model for Enhancer Activation Kinetics During Cell Differentiation -- Transcript Abundance Estimation and the Laminar Packing Problem -- Efficient Algorithms for Finding Edit-Distance Based Motifs.
This book constitutes the proceedings of the 6th InternationalConference on Algorithms for Computational Biology, AlCoB 2019, held in Berkeley, CA, USA, in May 2019. The 15 full papers presented together with 1 invited paper were carefully reviewed and selected from 30 submissions. They are organized in the following topical sections: Biological networks and graph algorithms; genome rearrangement, assembly and classification; sequence analysis, phylogenetics and other biological processes.
ISBN: 9783030181741
Standard No.: 10.1007/978-3-030-18174-1doiSubjects--Topical Terms:
893170
Computational biology
--Congresses.
LC Class. No.: QH324.2
Dewey Class. No.: 570.285
Algorithms for computational biology = 6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28-30, 2019 : proceedings /
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Invited Talk -- New Divide-and-Conquer Techniques for Large-Scale Phylogenetic Estimation -- Biological Networks and Graph Algorithms -- New Polynomial-Time Algorithm around the Scaffolding Problem -- Enumerating Dominant Pathways in Biological Networks by Information Flow Analysis -- Comparing Different Graphlet Measures for Evaluating Network Model Fits to BioGRID PPI Networks -- Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots -- PathRacer: Racing Profile HMM Paths on Assembly Graph -- Genome Rearrangement, Assembly and Classification -- A Uniform Theory of Adequate Subgraphs for the Genome Median, Halving, and Aliquoting Problems -- Lightweight Metagenomic Classification via eBWT -- MULKSG: MULtiple K Simultaneous Graph Assembly -- Counting Sorting Scenarios and Intermediate Genomes for the Rank Distance -- Generalizations of the Genomic Rank Distance to Indels -- Sequence Analysis, Phylogenetics and Other Biological Processes -- Using INC within Divide-and-Conquer Phylogeny Estimation -- Predicting Methylation from Sequence and Gene Expression Using Deep Learning with Attention -- A Mathematical Model for Enhancer Activation Kinetics During Cell Differentiation -- Transcript Abundance Estimation and the Laminar Packing Problem -- Efficient Algorithms for Finding Edit-Distance Based Motifs.
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