BICOB 2020: Volume InformationProceedings of the 12th International Conference on Bioinformatics and Computational Biology25 articles•246 pages•Published: March 11, 2020 PapersSection 1A: Cancer Research | Magali Champion, Julien Chiquet, Pierre Neuvial, Mohamed Elati, François Radvanyi and Etienne Birmelé 1-10 | Isis Narvaez-Bandera and Wandaliz Torres-Garcia 11-20 | Ankita Sahu, Dibyabhaba Pradhan, Khalid Raza, Sahar Qazi, A K Jain and Saurabh Verma 21-32 | Hsiu-Chuan Wei 33-40 | Section 1B: Machine Learning in Bioinformatics | Roberto Rosas Romero and Edgar Guevara 41-48 | Safa Shubbar, Chen Fu, Zhi Liu, Anthony Wynshaw-Boris and Qiang Guan 49-58 | Fardina Alam and Amarda Shehu 59-68 | Dylan Carpenter, Tess Thackray, Cecilia Kalthoff and Filip Jagodzinski 69-78 | Section 1C: Bioinformatics I | Andrew Smith, Glen Ropella and C. Anthony Hunt 79-88 | Daniel Berrios, Eric Weitz, Kirill Grigorev, Sylvain Costes, Samrawit Gebre and Afshin Beheshti 89-98 | Yuping Lu, Charles Phillips, Elissa Chesler and Michael Langston 99-108 | Mutlu Mete and Abdullah Arslan 109-118 | Section 2A: Genome Analysis | Pan Zhang, Bruce Southey and Sandra Rodriguez-Zas 119-128 | San Ha Seo and Saeed Salem 129-138 | Zhixiu Lu, Michael Gilchrist and Scott Emrich 139-148 | Ozgur Ekim Akman and Jonathan Edward Fieldsend 149-162 | Section 2B: Neural Networks and Predictive Approaches in Bioinformatics | Nicholas Leiby, Ayaan Hossain and Howard M Salis 163-172 | Xuyang Zhao, Linfeng Sui, Toshihisa Tanaka, Jianting Cao and Qibin Zhao 173-181 | Manpriya Dua, Daniel Barbara and Amarda Shehu 182-191 | Puzhou Wang 192-197 | Section 2C: Bioinformatics II | Preethi Krishnan, Lopamudra Dutta, Andrew Smith, Glen Ropella, Ryan Kennedy and Anthony Hunt 198-207 | Arun Govindaswamy, Wahhaj Farooq, Yiyang Wang, Ilyas Ustun, Daniela Raicu, Jacob Furst and Hongkyun Kim 208-216 | Lopamudra Dutta, Preethi Krishnan, Andrew Smith, Ryan Kennedy, Glen Ropella and C. Anthony Hunt 217-225 | Lawrence Yu-Min Liu, Zih-Yin Lai, Min-Hsuan Lin, Yu Shih and Yung-Jen Chuang 226-237 | Qin Yu, Geng Chen, Jiaqi Li, Xiaolong Liu, Xuegong Zhang and Haiming Lu 238-246 |
KeyphrasesADMET properties, Age-related research, agent-based, Aging, Analysis of high-throughput biological data, antimicrobial peptide recognition, Autism, Biclustering, bifurcation analysis, Bioinformatics2, Biological Data Clustering, Biomarker ALT release on Drug-Induced-Liver-Injury, Biomimetic Software Analogs, Boolean modelling, breast cancer2, C. elegans, CAI, cancer genomics, cancer systems biology, cellular exposure2, circadian clocks, cluster analysis, co-expression network, codon usage bias, computational biology2, Convolution Layer, Convolutional Neural Network2, COX-2 enzyme, Data Mining, deep learning, Deregulation, drug resistance, Dynamic Time Warping, Electroencephalogram, Epileptic focus localization, epileptic seizure prediction, Experiment Agent, feature fusion, Frequent Dense Modules, functional Near Infra-Red Spectroscopy, gene co-expression networks, gene expression, gene regulatory networks2, GeneLab, genotype, GPU, Graph Theoretical Algorithms, graphical lasso, Healthspan, heart regeneration, hepatic clearance, iEEG, in silico, in vitro-in vivo extrapolation, in vitro selection, LDA, lifespan, Liver Disease, machine learning, Magnetic Resonance Image, MCF-7, MD simulation, Medical Informatics, Microvascular Invasion, Model Mechanisms, modeling, mRNA abundance, multi-instance learning, multi-objective optimisation, multi-phase features, Mutaion Bias, NASA, nature-inspired computation, nematode, neural network, numerical method, numerical simulation, omics, Ontological Enrichment, parallel programming, pharmacokinetics, phenotype, PhGC, Prime MMGBSA, promoter, Protein-ligand complex, protein structure prediction, protein tertiary structure, Protein Translation Rate, Ramachandran plot, recurrent layer, rigidity analysis, RNA, RNA secondary structure, RNA sequencing, selection, sequence model, simulation2, spaceflight, Support Vector Machine, synthetic biology, systems biology, Tai, texture features, The Paraclique Algorithm, topic modeling, transcript-level, transcription rate, Transcriptomic Data Analysis, treatment-specific network, unsupervised learning, virtual experimentation, Virtual Liver, virtual screening, visualization, zebrafish. |
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