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Titlebook: Bioinformatics and Biomedical Engineering; 4th International Co Francisco Ortu?o,Ignacio Rojas Conference proceedings 2016 Springer Interna

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11#
發(fā)表于 2025-3-23 12:25:47 | 只看該作者
0302-9743 systems; highperformance computing in bioinformatics, computational biology andcomputational chemistry; human behavior monitoring, analysis and understanding;pattern recognition and machine learning in the -omics sciences; and resourcesfor bioinformatics..978-3-319-31743-4978-3-319-31744-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
12#
發(fā)表于 2025-3-23 14:25:54 | 只看該作者
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發(fā)表于 2025-3-23 21:06:30 | 只看該作者
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發(fā)表于 2025-3-24 01:15:43 | 只看該作者
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發(fā)表于 2025-3-24 18:30:49 | 只看該作者
,Hauptsache Haupts?tze - 1. Hauptsatz,sets relies on the design of appropriate algorithms and using them as the base to construct efficient data mining tools. Existing computational tools for MALDI-IMS exhibit numerous shortcomings and limited utility and cannot be used for fully automated discovery of heterogeneity in tumour samples. W
19#
發(fā)表于 2025-3-24 20:02:56 | 只看該作者
https://doi.org/10.1007/978-3-8348-9118-1value integration which includes the control of gene expression trend and introduces the adaptive significance level. What is more the multigene approach is proposed in contrary to classical single gene investigation. As a result, set of statistically significant polymorphisms was obtained, among wh
20#
發(fā)表于 2025-3-25 00:17:14 | 只看該作者
,Hauptsache Haupts?tze - 1. Hauptsatz,ificantly more accurate predictions than features selected from single source data (RNA-Seq data). Our study indicated that biological network-based feature transformation and data integration are two useful approaches to identify robust cancer biomarkers.
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