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Titlebook: Research in Computational Molecular Biology; 23rd Annual Internat Lenore J. Cowen Conference proceedings 2019 Springer Nature Switzerland A

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樓主: damped
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發(fā)表于 2025-3-25 05:15:32 | 只看該作者
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發(fā)表于 2025-3-25 10:21:03 | 只看該作者
Fast Approximation of Frequent ,-mers and Applications to Metagenomics, analysis. While several methods have been designed for the exact or approximate solution of this problem, they all require to process the entire dataset, that can be extremely expensive for high-throughput sequencing datasets. While in some applications it is crucial to estimate all .-mers and thei
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發(fā)表于 2025-3-25 15:02:34 | 只看該作者
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發(fā)表于 2025-3-25 19:10:11 | 只看該作者
A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer,given cancer genome are independent of one another. Recently, it was discovered that certain segments of mutations, termed processive groups, occur on the same DNA strand and are generated by a single process or signature. Here we provide a first probabilistic model of mutational signatures that acc
25#
發(fā)表于 2025-3-25 23:57:05 | 只看該作者
Disentangled Representations of Cellular Identity,ic basis vectors that are then decoded into gene expression levels. The basis vectors are learned with a deep autoencoder model from single-cell RNA-seq data. Linear arithmetic in the disentangled representation successfully predicts nonlinear gene expression interactions between biological pathways
26#
發(fā)表于 2025-3-26 02:30:50 | 只看該作者
RENET: A Deep Learning Approach for Extracting Gene-Disease Associations from Literature,ct knowledge from these articles to support research and genetic testing. In particular, the extraction of gene-disease associations is mostly studied. However, existing text-mining tools for extracting gene-disease associations have limited capacity, as each sentence is considered separately. Our e
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發(fā)表于 2025-3-26 07:46:20 | 只看該作者
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發(fā)表于 2025-3-26 18:33:22 | 只看該作者
0302-9743 hort abstracts are included in?the back matter of the volume. The papers report on original research in all?areas of computational molecular biology and bioinformatics..978-3-030-17082-0978-3-030-17083-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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