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001			233221
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007			cr nn 008mamaa
008			200817s2021 xxu| s |||| 0|eng d
020			_a9781071608265
024	7		_a10.1007/978-1-0716-0826-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aArtificial Neural Networks _cedited by Hugh Cartwright.
250			_a3rd edition 2021
264		1	_aNew York, NY _bSpringer International Publising _c2021
300			_a1 recurso en línea (XII, 359 páginas) _b134 ilustraciones, 114 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v2190
505	0		_aIdentifying Genotype-Phenotype Correlations via Integrative Mutation Analysis -- Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning -- Siamese Neural Networks: An Overview -- Computational Methods for Elucidating Gene Expression Regulation in Bacteria -- Neuro-evolutive Algorithms Applied for Modeling Some Biochemical Separation Processes -- Computational Approaches for de novo Drug Design: Past, Present, and Future -- Data Integration Using Advances in Machine Learning in Drug Discovery and Molecular Biology -- Building and Interpreting Artificial Neural Network Models for Biological Systems -- A Novel Computational Approach for Biomarker Detection for Gene Expression based Computer Aided Diagnostic Systems for Breast Cancer -- Applying Machine Learning for Integration of Multi-modal Genomics Data and Imaging Data to Quantify Heterogeneity in Tumour Tissues -- Leverage Large-scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning -- Predicting Host Phenotype based on Gut Microbiome using a Convolutional Neural Network Approach -- Predicting Hot-Spots using a Deep Neural Network Approach -- Using Neural Networks for Relation Extraction from Biomedical Literature -- A Hybrid Levenberg-Marquardt Algorithm on a Recursive Neural Network for Scoring Protein Models -- Secure and Scalable Collection of Biomedical Data for Machine Learning Applications -- AI-based Methods and Technologies to Develop Wearable Devices for Prosthetics and Predictions of Degenerative Diseases. .
520			_aThis 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.
700	1		_aCartwright, Hugh _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781071608258
776	0	8	_iPrinted edition: _z9781071608272
776	0	8	_iPrinted edition: _z9781071608289
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-0826-5 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2021
999			_c233221 _d233221