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Titlebook: Artificial Neural Networks; Hugh Cartwright Book 2021Latest edition Springer Science+Business Media, LLC, part of Springer Nature 2021 bio

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发表于 2025-3-21 16:23:13 | 显示全部楼层 |阅读模式
期刊全称Artificial Neural Networks
影响因子2023Hugh Cartwright
视频video
发行地址Includes cutting-edge methods and protocols.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from the experts?
学科分类Methods in Molecular Biology
图书封面Titlebook: Artificial Neural Networks;  Hugh Cartwright Book 2021Latest edition Springer Science+Business Media, LLC, part of Springer Nature 2021 bio
影响因子.This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover a wide variety of topics, including the analysis of intracellular sorting information, prediction of the behavior of bacterial communities, biometric authentication, studies of Tuberculosis, gene signatures in breast cancer classification, the use of mass spectrometry in metabolite identification, visual navigation, and computer diagnosis. Written in the highly successful .Methods in Molecular Biology. series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls... ..Authoritative and practical, .Artificial Neural Networks: Third Edition. should be of value to all scientists interested in the hands-on application of ANNs in the biosciences..
Pindex Book 2021Latest edition
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,Identifying Genotype–Phenotype Correlations via Integrative Mutation Analysis,ng variation within a gene. Here we present an overview of our integrative mutation analysis platform, which focuses on refining the current genotype–phenotype correlation methods by using the wealth of protein structural information.
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Siamese Neural Networks: An Overview,cosine distance. The output generated by a siamese neural network execution can be considered the semantic similarity between the projected representation of the two input vectors. In this overview we first describe the siamese neural network architecture, and then we outline its main applications i
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