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Titlebook: Discovering Biomolecular Mechanisms withComputational Biology; Frank Eisenhaber Book 2006 Springer-Verlag US 2006 Amino acid.DNA.Nucleotid

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樓主: PLY
21#
發(fā)表于 2025-3-25 05:14:03 | 只看該作者
22#
發(fā)表于 2025-3-25 10:37:11 | 只看該作者
Literature and Genome Data Mining for Prioritizing Disease-Associated Genesromosomal region to identify potential candidates that are scored using the precomputed associations. The scoring of associations between biological concepts using links across databases can be extended to other databases in Molecular Biology and to nondisease phenotypes.
23#
發(fā)表于 2025-3-25 11:45:45 | 只看該作者
24#
發(fā)表于 2025-3-25 16:02:32 | 只看該作者
The Predictive Power of Molecular Network Modellingl predictions on features of intracellular biological systems later. The three cases concern the optimal time course of gene expression in metabolic pathways, the operation of a metabolic route involving part of the tricarboxylic acid cycle and glyoxylate shunt, and the decoding of calcium oscillati
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發(fā)表于 2025-3-25 21:32:20 | 只看該作者
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發(fā)表于 2025-3-26 04:08:22 | 只看該作者
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發(fā)表于 2025-3-26 05:39:49 | 只看該作者
28#
發(fā)表于 2025-3-26 08:44:00 | 只看該作者
1431-0414 ce researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success. .978-1-4419-4177-0978-0-387-36747-7Series ISSN 1431-0414
29#
發(fā)表于 2025-3-26 15:13:18 | 只看該作者
https://doi.org/10.1007/978-3-8349-4359-0ortant questions. Currendy, theoretical methods have best chances to contribute to new biological insight independently of experiments in the area of genome text interpretation and especially for gene function prediction. Experimental studies can help progress in the development of theoretical metho
30#
發(fā)表于 2025-3-26 17:13:03 | 只看該作者
https://doi.org/10.1007/978-3-8349-4359-0t-based function prediction provide complementary information about a protein’s function and can becombined to make predictions that are specific enough for experimental testing. Here we discuss the genomic coverage and reliability of combining genomics data for protein function prediction and surve
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