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ORCIDArtificial Neural Networks, Third Edition, 2021
- Hugh M. Cartwright:
Artificial Neural Networks - Third Edition. Methods in Molecular Biology 2190, Springer 2021, ISBN 978-1-0716-0825-8 - Edward Airey, Stephanie Portelli
, Joicymara S. Xavier, Yoochan Myung, Michael Silk, Malancha Karmakar, João P. L. Velloso, Carlos H. M. Rodrigues, Hardik H. Parate, Anjali Garg, Raghad Al-Jarf, Lucy Barr, Juliana A. Geraldo, Pâmela M. Rezende, Douglas E. V. Pires, David B. Ascher:
Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis. 1-32 - Christian Bock, Michael Moor, Catherine R. Jutzeler, Karsten M. Borgwardt:
Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning. 33-71 - Davide Chicco:
Siamese Neural Networks: An Overview. 73-94 - Kratika Naskulwar, Ruben Chevez-Guardado, Lourdes Peña Castillo:
Computational Methods for Elucidating Gene Expression Regulation in Bacteria. 95-114 - Silvia Curteanu, Elena Niculina Dragoi, Alexandra Cristina Blaga, Anca-Irina Galaction, Dan Cascaval:
Neuroevolutive Algorithms Applied for Modeling Some Biochemical Separation Processes. 115-138 - Xuhan Liu, Adriaan P. IJzerman, Gerard J. P. van Westen:
Computational Approaches for De Novo Drug Design: Past, Present, and Future. 139-165 - Irene Lena Hudson:
Data Integration Using Advances in Machine Learning in Drug Discovery and Molecular Biology. 167-184 - T. Murlidharan Nair:
Building and Interpreting Artificial Neural Network Models for Biological Systems. 185-194 - Ali Al-Yousef, Sandhya Samarasinghe:
A Novel Computational Approach for Biomarker Detection for Gene Expression-Based Computer-Aided Diagnostic Systems for Breast Cancer. 195-208 - Xiao Tan, Andrew Su, Hamideh Hajiabadi, Minh Tran, Quan Nguyen:
Applying Machine Learning for Integration of Multi-Modal Genomics Data and Imaging Data to Quantify Heterogeneity in Tumour Tissues. 209-228 - Hao Wang, Jiaxin Yang, Jianrong Wang:
Leverage Large-Scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning. 229-248 - Derek Reiman, Ali M. Farhat, Yang Dai:
Predicting Host Phenotype Based on Gut Microbiome Using a Convolutional Neural Network Approach. 249-266 - António J. Preto, Pedro Matos-Filipe, José G. de Almeida, Joana Mourão, Irina S. Moreira:
Predicting Hot Spots Using a Deep Neural Network Approach. 267-288 - Diana F. Sousa, Andre Lamurias, Francisco M. Couto:
Using Neural Networks for Relation Extraction from Biomedical Literature. 289-305 - Eshel Faraggi, Robert L. Jernigan, Andrzej Kloczkowski:
A Hybrid Levenberg-Marquardt Algorithm on a Recursive Neural Network for Scoring Protein Models. 307-316 - Charles Fracchia:
Secure and Scalable Collection of Biomedical Data for Machine Learning Applications. 317-336 - Mario Malcangi:
AI-Based Methods and Technologies to Develop Wearable Devices for Prosthetics and Predictions of Degenerative Diseases. 337-354
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