arXiv Quantitative Biology @arxiv_bio@qoto.org

Universal relation between instantaneous diffusivity and radius of gyration of proteins in aqueous solution. (arXiv:2009.06829v1 [cond-mat.stat-mech]) http://arxiv.org/abs/2009.06829

Co-evolution of Functional Brain Network at Multiple Scales during Early Infancy. (arXiv:2009.06899v1 [q-bio.NC]) http://arxiv.org/abs/2009.06899

Hierarchical Coarse-grained Approach to the Duration-dependent Spreading Dynamics in Complex Networks. (arXiv:2009.06919v1 [cond-mat.stat-mech]) http://arxiv.org/abs/2009.06919

Machine learning predicts early onset of fever from continuous physiological data of critically ill patients. (arXiv:2009.07103v1 [q-bio.QM]) http://arxiv.org/abs/2009.07103

Flexibility of brain regions during working memory curtails cognitive consequences to lack of sleep. (arXiv:2009.07233v1 [q-bio.NC]) http://arxiv.org/abs/2009.07233

Cognitive State Analysis, Understanding, and Decoding from the Perspective of Brain Connectivity. (arXiv:2005.12191v2 [q-bio.NC] UPDATED) http://arxiv.org/abs/2005.12191

A Physics Modeling Study of SARS-CoV-2 Transport in Air. (arXiv:2007.05410v3 [physics.bio-ph] UPDATED) http://arxiv.org/abs/2007.05410

The challenges of containing SARS-CoV-2 via test-trace-and-isolate. (arXiv:2009.05732v1 [q-bio.PE]) http://arxiv.org/abs/2009.05732

Realistic estimate of the cumulative and instantaneous Covid-19 incidence in France. (arXiv:2009.05749v1 [q-bio.PE]) http://arxiv.org/abs/2009.05749

Machine Learning Against Cancer: Accurate Diagnosis of Cancer by Machine Learning Classification of the Whole Genome Sequencing Data. (arXiv:2009.05847v1 [q-bio.GN]) http://arxiv.org/abs/2009.05847

Network analysis and disease subnets for the SARS-CoV-2/Human interactome. (arXiv:2009.06035v1 [q-bio.MN]) http://arxiv.org/abs/2009.06035

Stochastic Turing pattern formation in a model with active and passive transport. (arXiv:2009.06076v1 [cond-mat.stat-mech]) http://arxiv.org/abs/2009.06076

Directional search-and-capture model of cytoneme-based morphogenesis. (arXiv:2009.06095v1 [cond-mat.stat-mech]) http://arxiv.org/abs/2009.06095

Simple Learning Rules Generate Complex Canonical Circuits. (arXiv:2009.06118v1 [q-bio.NC]) http://arxiv.org/abs/2009.06118

Finding Acceptable Parameter Regions of Stochastic Hill functions for Multisite Phosphorylation Mechanism. (arXiv:2009.06313v1 [q-bio.MN]) http://arxiv.org/abs/2009.06313

3-D macro/microporous-nanofibrous bacterial cellulose scaffolds seeded with BMP-2 preconditioned mesenchymal stem cells exhibit remarkable potential for bone tissue engineering. (arXiv:2009.06338v1 [q-bio.BM]) http://arxiv.org/abs/2009.06338

Projections for COVID-19 spread in India and its worst affected five states using the Modified SEIRD and LSTM models. (arXiv:2009.06457v1 [q-bio.PE]) http://arxiv.org/abs/2009.06457

AFP-SRC: Identification of Antifreeze Proteins Using Sparse Representation Classifier. (arXiv:2009.05277v1 [cs.CV]) http://arxiv.org/abs/2009.05277

Infection Kinetics of Covid-19: Is Lockdown a Potent Containment Tool?. (arXiv:2009.05280v1 [q-bio.QM]) http://arxiv.org/abs/2009.05280

Temporal Analysis of COVID-19 Peak Outbreak. (arXiv:2009.05285v1 [q-bio.PE]) http://arxiv.org/abs/2009.05285