Computational Advances in Bio and Medical Sciences by Alser, Mohammed; Bansal, Mukul S.; Khudyakov, Yury;

Hosszú leírás:

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This book constitutes the refereed proceedings of the 13th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2025, held in Atlanta, GA, USA, during January 12–14, 2025.

The 26 full papers presented in these proceedings were carefully reviewed and selected from 75 submissions. ICCABS has the goal of bringing together researchers, scientists, and students from academia, laboratories, and industry to discuss recent advances on computational techniques and applications in the areas of biology, medicine, and drug discovery.

Tartalomjegyzék:

.- A Benchmarking Study of Random Projections and Principal Components for Dimensionality Reduction Strategies in Single Cell Analysis.

.- Resistance genes are distinct in protein-protein interaction networks according to drug class and gene mobility.

.- DuoHash: fast hashing of spaced seeds with application to spaced k-mers counting.

.- Unsupervised Learning for Tertiary Structure Prediction of Protein Molecules: Systematic Review.

.- Fast and Succinct Compression of k-mer Sets with Plain Text Representation of Colored de Bruijn Graphs.

.- Enhancing Protein Side Chain Packing Using Rotamer Clustering and Machine Learning.

.- Can Language Models Reason about ICD Codes to Guide the Generation of Clinical Notes?.

.- Link Prediction in Disease-Disease Interactions Network Using a Hybrid Deep Learning Model.

.- Model Selection for Sparse Microbial Network Inference using Variational Approximation.

.- Haplotype-based Parallel PBWT for Biobank Scale Data.

.- Mammo-Bench: A Large-scale Benchmark Dataset of Mammography Images.

.- MetaEdit: Computational Identification of RNA editing in Microbiomes.

.- Drug-centric prior improves drug response modeling in partially overlapping pharmacogenomic screens.

.- Improving inter-helical residue contact prediction in α-helical Transmembrane proteins using structural neighborhood crowdedness information.

.- Explaining Protein Folding Networks Using Integrated Gradients and Attention Mechanisms.

.- The evolution of cancer progression risk: a phylogenetic and machine learning analysis.

.- Cancer Diseases Classification with Sparse Neural Networks: An Information-Theoretic Approach.

.- Epistatic Density of Viral Variants in Acute and Chronic HCV patients.

.- Applying Genetic Algorithm with Saltations to MAX-3SAT.

.- Computing Gram Matrix for SMILES Strings using RDKFingerprint and Sinkhorn-Knopp Algorithm.

.- Enhancing Privacy Preservation and Reducing Analysis Time with Federated Transfer Learning in Digital Twins-based CT Scan Analysis.

.- Improved Graph-Based Antibody-Aware Epitope Prediction with Protein Language Model-Based Embeddings.

.- Leveraging RNA LLMs for 3D Structure Prediction via Novel Data Augmentation.

.- EfficientNet in Digital Twin-based Cardiac Arrest Prediction and Analysis.

.- AmpliconHunter: A Scalable Tool for Accurate Amplicon Prediction from Microbiome Samples using Degenerate Primers.

.- Neuromorphic Spiking Neural Network Based Classification of COVID-19 Spike Sequences.