arXiv Quantitative Biology @arxiv_bio@qoto.org

LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction https://arxiv.org/abs/2407.16709 #qbioGN #csLG

Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learning https://arxiv.org/abs/2407.16715 #qbioQM #csAI #csLG

Machine Learning Models for the Identification of Cardiovascular Diseases Using UK Biobank Data https://arxiv.org/abs/2407.16721 #qbioQM #csLG

Chemistry-informed Machine Learning Explains Calcium-binding Proteins Fuzzy Shape for Communicating Changes in the Atomic States of Calcium Ions https://arxiv.org/abs/2407.17017 #qbioQM

Optimization of breeding program design through stochastic simulation with evolutionary algorithms https://arxiv.org/abs/2407.17286 #qbioQM #csNE

Neural field equations with time-periodic external inputs and some applications to visual processing https://arxiv.org/abs/2407.17294 #qbioNC #mathAP #mathDS #mathOC

Physical limits on galvanotaxis depends on cell morphology and orientation https://arxiv.org/abs/2407.17420 #physicsbioph #condmatsoft #qbioCB

q-deformed evolutionary dynamics in simple matrix games https://arxiv.org/abs/2407.16380 #cond-mat.stat-mech #physics.soc-ph #qbioPE

A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms https://arxiv.org/abs/2407.16727 #qbioQM #cs.CV

GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning https://arxiv.org/abs/2407.16940 #qbioGN #cs.LG

A Benchmark Dataset for Multimodal Prediction of Enzymatic Function Coupling DNA Sequences and Natural Language https://arxiv.org/abs/2407.15888 #qbioGN #csLG

The Genomic Code: The genome instantiates a generative model of the organism https://arxiv.org/abs/2407.15908 #qbioOT

A statistical significance test for spatio-temporal receptive field estimates obtained using spike-triggered averaging of binary pseudo-random sequences https://arxiv.org/abs/2407.16013 #qbioQM #qbioNC

Hierarchical Machine Learning Classification of Parkinsonian Disorders using Saccadic Eye Movements: A Development and Validation Study https://arxiv.org/abs/2407.16063 #qbioQM #qbioNC

Modelling brain connectomes networks: Solv is a worthy competitor to hyperbolic geometry! https://arxiv.org/abs/2407.16077 #qbioNC #mathMG #csAI

Energy-information trade-off makes the cortical critical power law the optimal coding https://arxiv.org/abs/2407.16215 #qbioNC

How Does a Single EEG Channel Tell Us About Brain States in Brain-Computer Interfaces ? https://arxiv.org/abs/2407.16249 #qbioNC

Ranking protein-protein models with large language models and graph neural networks https://arxiv.org/abs/2407.16375 #qbioBM #csAI

Assessment of scoring functions for computational models of protein-protein interfaces https://arxiv.org/abs/2407.16580 #qbioBM

The need to implement FAIR principles in biomolecular simulations https://arxiv.org/abs/2407.16584 #qbioBM