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September 2023

Multi-decade efforts have yielded voltage gating voltage (∆V1/2) data on almost 500 single mutants of the big potassium (BK) channel. The left panel shows all residues of the BK channel where at least one mutation has been characterized experimentally. While representing enormous efforts, these data alone remain too scarce for deriving quantitative models for predicting the mutational effects using data-driven machine learning approaches. By incorporating physical features derived from molecular modeling and simulations, we show that a random forest model trained using 80% of the experimental shift in gating voltage is able to predict unseen experimental data with 0.79 correlation. The model is also able to capture a central role of hydrophobic gating in BK channels as well as new experimental results on several novel mutations. Nordquist et al 2023

Image Credit: Erik Nordquist, enordquist@umass.edu

Education Articles

Fourteen quick tips for crowdsourcing geographically linked data for public health advocacy

Joshua Atienza, Anjalee Benedict, Lincoln D. Stein, Kashif Pirzada, Cheryl White, Shraddha Pai

Ten simple rules for interpreting and evaluating a meta-analysis

Rebecca B. Carlson, Jennifer R. Martin, Robert D. Beckett

Ten quick tips for building FAIR workflows

Casper de Visser, Lennart F. Johansson, Purva Kulkarni, Hailiang Mei, Pieter Neerincx, K. Joeri van der Velde, Péter Horvatovich, Alain J. van Gool, Morris A. Swertz, Peter A. C. ‘t Hoen, Anna Niehues

Research Articles

Bayesian inference for spatio-temporal stochastic transmission of plant disease in the presence of roguing: A case study to characterise the dispersal of Flavescence dorée

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Dynamical modelling of viral infection and cooperative immune protection in COVID-19 patients

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Evaluating the impact of test-trace-isolate for COVID-19 management and alternative strategies

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Self-loops in evolutionary graph theory: Friends or foes?

Nikhil Sharma, Sedigheh Yagoobi, Arne Traulsen

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics

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RSim: A reference-based normalization method via rank similarity

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Age-differentiated incentives for adaptive behavior during epidemics produce oscillatory and chaotic dynamics

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The inhibitory control of traveling waves in cortical networks

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Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks

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iCVS—Inferring Cardio-Vascular hidden States from physiological signals available at the bedside

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What constrains food webs? A maximum entropy framework for predicting their structure with minimal biases

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An automated interface for sedimentation velocity analysis in SEDFIT

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Controlling brain dynamics: Landscape and transition path for working memory

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A whole-task brain model of associative recognition that accounts for human behavior and neuroimaging data

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Christopher L. Hewitson, David M. Kaplan, Matthew J. Crossley

Emergence of belief-like representations through reinforcement learning

Jay A. Hennig, Sandra A. Romero Pinto, Takahiro Yamaguchi, Scott W. Linderman, Naoshige Uchida, Samuel J. Gershman

iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease

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Pathfinder: Protein folding pathway prediction based on conformational sampling

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OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates

Shuming Liu, Cong Wang, Andrew P. Latham, Xinqiang Ding, Bin Zhang

Testing predictive coding theories of autism spectrum disorder using models of active inference

Tom Arthur, Sam Vine, Gavin Buckingham, Mark Brosnan, Mark Wilson, David Harris

Simulation-based Reconstructed Diffusion unveils the effect of aging on protein diffusion in Escherichia coli

Luca Mantovanelli, Dmitrii S. Linnik, Michiel Punter, Hildeberto Jardón Kojakhmetov, Wojciech M. Śmigiel, Bert Poolman

Classification of T lymphocyte motility behaviors using a machine learning approach

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Evaluating the use of social contact data to produce age-specific short-term forecasts of SARS-CoV-2 incidence in England

James D. Munday, Sam Abbott, Sophie Meakin, Sebastian Funk

Beyond 1 sparse coding in V1

Ilias Rentzeperis, Luca Calatroni, Laurent U. Perrinet, Dario Prandi

Uncovering specific mechanisms across cell types in dynamical models

Adrian L. Hauber, Marcus Rosenblatt, Jens Timmer

Mixtures of strategies underlie rodent behavior during reversal learning

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Incorporating physics to overcome data scarcity in predictive modeling of protein function: A case study of BK channels

Erik Nordquist, Guohui Zhang, Shrishti Barethiya, Nathan Ji, Kelli M. White, Lu Han, Zhiguang Jia, Jingyi Shi, Jianmin Cui, Jianhan Chen

Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model

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Human-environment feedback and the consistency of proenvironmental behavior

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Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Serena Aneli, Piero Fariselli, Elena Chierto, Carla Bini, Carlo Robino, Giovanni Birolo

Marginal effects of public health measures and COVID-19 disease burden in China: A large-scale modelling study

Zengmiao Wang, Peiyi Wu, Lin Wang, Bingying Li, Yonghong Liu, Yuxi Ge, Ruixue Wang, Ligui Wang, Hua Tan, Chieh-Hsi Wu, Marko Laine, Henrik Salje, Hongbin Song

Nowcasting the 2022 mpox outbreak in England

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Exploring tumor-normal cross-talk with TranNet: Role of the environment in tumor progression

Bayarbaatar Amgalan, Chi-Ping Day, Teresa M. Przytycka

The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

Emanuel Cunha, Miguel Silva, Inês Chaves, Huseyin Demirci, Davide Rafael Lagoa, Diogo Lima, Miguel Rocha, Isabel Rocha, Oscar Dias

Mechanistic multiscale modelling of energy metabolism in human astrocytes reveals the impact of morphology changes in Alzheimer’s Disease

Sofia Farina, Valérie Voorsluijs, Sonja Fixemer, David S. Bouvier, Susanne Claus, Mark H. Ellisman, Stéphane P. A. Bordas, Alexander Skupin

Identifying a developmental transition in honey bees using gene expression data

Bryan C. Daniels, Ying Wang, Robert E. Page Jr, Gro V. Amdam

A platform-independent framework for phenotyping of multiplex tissue imaging data

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Personalized prediction for multiple chronic diseases by developing the multi-task Cox learning model

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Likelihood-ratio test statistic for the finite-sample case in nonlinear ordinary differential equation models

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Simulation-based inference for efficient identification of generative models in computational connectomics

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CIRCUST: A novel methodology for temporal order reconstruction of molecular rhythms; validation and application towards a daily rhythm gene expression atlas in humans

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Integrating a tailored recurrent neural network with Bayesian experimental design to optimize microbial community functions

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Software

Trackplot: A flexible toolkit for combinatorial analysis of genomic data

Yiming Zhang, Ran Zhou, Lunxu Liu, Lu Chen, Yuan Wang