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ORCIDCIBCB 2021: Melbourne, Australia
- Jennifer Hallinan, Madhu Chetty, Gonzalo Ruz Heredia, Adrian Shatte, Suryani Lim:
IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021, Melbourne, Australia, October 13-15, 2021. IEEE 2021, ISBN 978-1-6654-0112-8 - Simone Spolaor
, Daniele M. Papetti, Paolo Cazzaniga, Daniela Besozzi, Marco S. Nobile:
A comparison of multi-objective optimization algorithms to identify drug target combinations. 1-8 - Chen Lam Loh, Tom Froese:
An Oscillator Model for Interbrain Synchrony: Slow Interactional Rhythms Entrain Fast Neural Activity. 1-8 - Ravindra Kumar, Anjali Garg, Bandana Kumari, Aakriti Jain, Manish Kumar, Equal Contribution:
Identification of chloroplast and sub-chloroplast proteins from sequence-attributed features using support vector machine and domain information. 1-9 - Joseph Livesey, Dominik Wojtczak:
Leveraging Neural Networks in Malaria Control. 1-6 - Enoch S. Liu, Gary B. Fogel, David J. Nolan, Susanna L. Lamers, Michael S. McGrath:
Using Evolved Neural Networks to Elucidate Nef Features Associated with HIV-1 Subtype Differentiation. 1-8 - Farhan Tanvir, Muhammad Ifte Islam, Esra Akbas:
Predicting Drug-Drug Interactions Using Meta-path Based Similarities. 1-8 - Tamasha Malepathirana, Damith A. Senanayake, Vini Gautam, Saman K. Halgamuge:
Robustness of Visualization Methods in Preserving the Continuous and Discrete Latent Structures of High-Dimensional Single-Cell Data. 1-9 - Shunya Sugita, Masahito Ohue:
Drug-target affinity prediction using applicability domain based on data density. 1-6 - Veena Mayya, S. Sowmya Kamath, Vijayan Sugumaran:
$\mathcal{LAJA}{-}$ Label Attention Transformer Architectures for ICD-10 Coding of Unstructured Clinical Notes. 1-7 - Batuhan Bardak, Mehmet Tan:
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions. 1-8 - Alberto Zancanaro, Giulia Cisotto, João Ruivo Paulo, Gabriel Pires, Urbano J. Nunes:
CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From the State-of-The-Art to DynamicNet. 1-7 - J. Siva Ramakrishna, Neelam Sinha, Hariharan Ramasangu:
Classification of Human Emotions using EEG-based Causal Connectivity Patterns. 1-8 - Mohimenul Karim, Rashid Abid:
Efficacy and accuracy responses of DNA mini-barcodes in species identification under a supervised machine learning approach. 1-9 - Daniel A. Ashlock, Michael Dubé:
A Comparison of Novel Representations for Evolving Epidemic Networks. 1-8 - Dacosta Yeboah, Hung Nguyen, Daniel B. Hier, Gayla R. Olbricht, Tayo Obafemi-Ajayi:
A deep learning model to predict traumatic brain injury severity and outcome from MR images. 1-6 - Jaspreet Singh, Jaswinder Singh, Kuldip K. Paliwal, Andrew Busch, Yaoqi Zhou:
SPOT-1D2: Improving Protein Secondary Structure Prediction using High Sequence Identity Training Set and an Ensemble of Recurrent and Residual-convolutional Neural Networks. 1-7 - Fatemeh ZareMehrjardi, Athar Omidi, Cristina Sciortino, Ryan E. R. Reid, Ryan Lukeman, James Alexander Hughes, Othman Soufan:
Discovering Missing Edges in Drug-Protein Networks: Repurposing Drugs for SARS-CoV-2. 1-10 - Daniel A. Ashlock, Joseph Alexander Brown, Sheridan K. Houghten, Munir Makhmutov:
One Moose, Two Moose, Three Fields, More? 1-7 - Guangyao Chen, James Sargant, Sheridan K. Houghten, Tyler Kennedy Collins:
Identification of Genes Associated with Alzheimer's Disease using Evolutionary Computation. 1-9 - Hasini Nakulugamuwa Gamage, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
An Efficient Boolean Modelling Approach for Genetic Network Inference. 1-8 - Daniel A. Ashlock, Joseph Alexander Brown, Wendy Ashlock, Michael Dubé:
Ring Optimization of Epidemic Contact Networks. 1-8 - Taki Hasan Rafi, Raed M. Shubair:
A Scaled-2D CNN for Skin Cancer Diagnosis. 1-6 - Surbhi Gupta, Manoj Kumar Gupta:
Deep Learning for Brain Tumor Segmentation using Magnetic Resonance Images. 1-6 - Qi Tian, Jianxiao Zou, Jianxiong Tang, Shicai Fan:
Multi-distance based spectral embedding fusion for clustering single-cell methylation data. 1-8 - Gülüstan Dogan, Sinem Sena Ertas, Iremnaz Cay:
Human Activity Recognition Using Convolutional Neural Networks. 1-5 - Bill Yang, Goksel Misirli, Anil Wipat, Jennifer Hallinan:
Modelling The Fitness Landscapes of a SCRaMbLEd Yeast Genome. 1-9 - Jongwoo Kim, Loc Q. Tran:
Retinal Disease Classification from OCT Images Using Deep Learning Algorithms. 1-6 - Benan Bardak, Mehmet Tan:
DeepGREP: A deep convolutional neural network for predicting gene-regulating effects of small molecules. 1-8 - Takatsugi Kosugi, Masahito Ohue:
Quantitative Estimate of Protein-Protein Interaction Targeting Drug-likeness. 1-8 - Anik Das, Sumaiya Amin, James Alexander Hughes:
Automatic Detection of Necrotizing Fasciitis: A Dataset and Early Results. 1-8 - Miria Bernardino, Robert G. Beiko:
Genome-scale prediction of bacterial promoters. 1-8 - Nabila Sekar Ramadhanti, Wisnu Ananta Kusuma, Irmanida Batubara, Rudi Heryanto:
Random Forest to Predict Eucalyptus as a Potential Herb in Preventing Covid19. 1-5 - Sumaiya Amin, Sheridan K. Houghten, James Alexander Hughes:
Vaccinating a Population is a Changing Programming Problem. 1-10 - Trinh Van Giang, Kunihiko Hiraishi:
An Improved Method for Finding Attractors of Large-Scale Asynchronous Boolean Networks. 1-9 - Sheriff Abouchekeir, Alain B. Tchagang, Yifeng Li:
Adversarial Deep Evolutionary Learning for Drug Design. 1-9 - Jaskaran Gill, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
Dynamically Regulated Initialization for S-system Modelling of Genetic Networks. 1-8 - Yanhua Xu, Dominik Wojtczak:
Predicting Influenza A Viral Host Using PSSM and Word Embeddings. 1-10
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