From predictions to prescriptions: A data-driven response to COVID-19. (arXiv:2006.16509v1 [stat.AP]) http://arxiv.org/abs/2006.16509
Hunting Co-operation in the Middle Predator in Three Species Food Chain Model. (arXiv:2006.16525v1 [q-bio.PE]) http://arxiv.org/abs/2006.16525
Computing extracellular electric potentials from neuronal simulations. (arXiv:2006.16630v1 [q-bio.NC]) http://arxiv.org/abs/2006.16630
Associations between finger tapping, gait and fall risk with application to fall risk assessment. (arXiv:2006.16648v1 [q-bio.QM]) http://arxiv.org/abs/2006.16648
C19-TraNet: an empirical, global index-case transmission network of SARS-CoV-2. (arXiv:2006.15162v1 [q-bio.PE]) http://arxiv.org/abs/2006.15162
BERTology Meets Biology: Interpreting Attention in Protein Language Models. (arXiv:2006.15222v1 [cs.CL]) http://arxiv.org/abs/2006.15222
Smile-GANs: Semi-supervised clustering via GANs for dissecting brain disease heterogeneity from medical images. (arXiv:2006.15255v1 [q-bio.QM]) http://arxiv.org/abs/2006.15255
The COVID-19 (SARS-CoV-2) Uncertainty Tripod in Brazil: Assessments on model-based predictions with large under-reporting. (arXiv:2006.15268v1 [q-bio.PE]) http://arxiv.org/abs/2006.15268
Spatio-temporal predictive modeling framework for infectious disease spread. (arXiv:2006.15336v1 [q-bio.PE]) http://arxiv.org/abs/2006.15336
Methodology for Modelling the new COVID-19 Pandemic Spread and Implementation to European Countries. (arXiv:2006.15385v1 [q-bio.PE]) http://arxiv.org/abs/2006.15385
Using micro- and macro-level network metrics unveils top communicative gene modules in psoriasis. (arXiv:2006.15414v1 [q-bio.GN]) http://arxiv.org/abs/2006.15414
Fast automatic segmentation of thalamic nuclei from MP2RAGE acquisition at 7 Tesla. (arXiv:2006.15460v1 [eess.IV]) http://arxiv.org/abs/2006.15460
Polymerase/nicking enzyme powered dual-template multi-cycled G-triplex machine for HIV-1 determination. (arXiv:2006.15548v1 [q-bio.QM]) http://arxiv.org/abs/2006.15548
Modelling Excess Mortality in Covid-19-like Epidemics. (arXiv:2006.15583v1 [physics.soc-ph]) http://arxiv.org/abs/2006.15583
What the reproductive number R_0 can and cannot tell us about COVID-19 dynamics. (arXiv:2006.14676v1 [q-bio.PE]) http://arxiv.org/abs/2006.14676
Active Learning Pipeline for Brain Mapping in a High Performance Computing Environment. (arXiv:2006.14684v1 [eess.IV]) http://arxiv.org/abs/2006.14684
A Computational Model of Protein Induced Membrane Morphology with Geodesic Curvature Driven Protein-Membrane Interface. (arXiv:2006.14685v1 [cond-mat.soft]) http://arxiv.org/abs/2006.14685
Machine-Learning Driven Drug Repurposing for COVID-19. (arXiv:2006.14707v1 [cs.LG]) http://arxiv.org/abs/2006.14707
Prediction of the Number of COVID-19 Confirmed Cases Based on K-Means-LSTM. (arXiv:2006.14752v1 [q-bio.PE]) http://arxiv.org/abs/2006.14752
Drug Repurposing to find Inhibitors of SARS-CoV-2 Main Protease. (arXiv:2006.14790v1 [q-bio.BM]) http://arxiv.org/abs/2006.14790
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