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May 2023

The cat (C-A-T) on the image represents the condensation (C), adenylation (A), and thiolation (T) domains that constitute the basic module of the non-ribosomal peptide synthetase (NRPS). Each module selects a specific substrate, represented by the ball on the cat’s head, and the train of cats represents the NRPS assembly line. The peptide product of NRPS (a string of balls) is placed on the right. The standardized architecture with conserved motifs was displayed as a ruler around the assembly line. In our publication, standardization of NRPS is achieved by NRPS Motif Finder. He et al. 2023

Image Credit: Rezin Ghost

Education

Four guiding principles for effective trainee-led STEM community engagement through high school outreach

Stefanie Luecke, Allison Schiffman, Apeksha Singh, Helen Huang, Barbara Shannon, Catera L. Wilder

Research Articles

Data-driven segmentation of cortical calcium dynamics

Sydney C. Weiser, Brian R. Mullen, Desiderio Ascencio, James B. Ackman

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning

Olga Mineeva, Daniel Danciu, Bernhard Schölkopf, Ruth E. Ley, Gunnar Rätsch, Nicholas D. Youngblut

Predicting anti-cancer drug combination responses with a temporal cell state network model

Deepraj Sarmah, Wesley O. Meredith, Ian K. Weber, Madison R. Price, Marc R. Birtwistle

Coherent noise enables probabilistic sequence replay in spiking neuronal networks

Younes Bouhadjar, Dirk J. Wouters, Markus Diesmann, Tom Tetzlaff

Predicting partner fitness based on spatial structuring in a light-driven microbial community

Jonathan K. Sakkos, María Santos-Merino, Emmanuel J. Kokarakis, Bowen Li, Miguel Fuentes-Cabrera, Paolo Zuliani, Daniel C. Ducat

An integrated model for predicting KRAS dependency

Yihsuan S. Tsai, Yogitha S. Chareddy, Brandon A. Price, Joel S. Parker, Chad V. Pecot

A unitary mechanism underlies adaptation to both local and global environmental statistics in time perception

Tianhe Wang, Yingrui Luo, Richard B. Ivry, Jonathan S. Tsay, Ernst Pöppel, Yan Bao

Target-agnostic drug prediction integrated with medical record analysis uncovers differential associations of statins with increased survival in COVID-19 patients

Megan M. Sperry, Tomiko T. Oskotsky, Ivana Marić, Shruti Kaushal, Takako Takeda, Viktor Horvath, Rani K. Powers, Melissa Rodas, Brooke Furlong, Mercy Soong, Pranav Prabhala, Girija Goyal, Kenneth E. Carlson, Ronald J. Wong, Idit Kosti, Brian L. Le, James Logue, Holly Hammond, Matthew Frieman, David K. Stevenson, Donald E. Ingber, Marina Sirota, Richard Novak

Matrix prior for data transfer between single cell data types in latent Dirichlet allocation

Alan Min, Timothy Durham, Louis Gevirtzman, William Stafford Noble

Modeling the impact of xenointoxication in dogs to halt Trypanosoma cruzi transmission

Jennifer L. Rokhsar, Brinkley Raynor, Justin Sheen, Neal D. Goldstein, Michael Z. Levy, Ricardo Castillo-Neyra

Noise improves the association between effects of local stimulation and structural degree of brain networks

Yi Zheng, Shaoting Tang, Hongwei Zheng, Xin Wang, Longzhao Liu, Yaqian Yang, Yi Zhen, Zhiming Zheng

Temporal novelty detection and multiple timescale integration drive Drosophila orientation dynamics in temporally diverse olfactory environments

Viraaj Jayaram, Aarti Sehdev, Nirag Kadakia, Ethan A. Brown, Thierry Emonet

Learning to predict future locations with internally generated theta sequences

Eloy Parra-Barrero, Sen Cheng

Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19

Sarafa A. Iyaniwura, Notice Ringa, Prince A. Adu, Sunny Mak, Naveed Z. Janjua, Michael A. Irvine, Michael Otterstatter

Self-assembly coupled to liquid-liquid phase separation

Michael F. Hagan, Farzaneh Mohajerani

Modelling novelty detection in the thalamocortical loop

Chao Han, Gwendolyn English, Hannes P. Saal, Giacomo Indiveri, Aditya Gilra, Wolfger von der Behrens, Eleni Vasilaki

Knowledge-guided data mining on the standardized architecture of NRPS: Subtypes, novel motifs, and sequence entanglements

Ruolin He, Jinyu Zhang, Yuanzhe Shao, Shaohua Gu, Chen Song, Long Qian, Wen-Bing Yin, Zhiyuan Li

Targeting operational regimes of interest in recurrent neural networks

Pierre Ekelmans, Nataliya Kraynyukova, Tatjana Tchumatchenko

Binding pocket dynamics along the recovery stroke of human β-cardiac myosin

Fariha Akter, Julien Ochala, Arianna Fornili

Structure learning for gene regulatory networks

Anthony Federico, Joseph Kern, Xaralabos Varelas, Stefano Monti

An approximate diffusion process for environmental stochasticity in infectious disease transmission modelling

Sanmitra Ghosh, Paul J. Birrell, Daniela De Angelis

Stochastic modelling of a three-dimensional glycogen granule synthesis and impact of the branching enzyme

Yvan Rousset, Oliver Ebenhöh, Adélaïde Raguin

Modelling the structures of frameshift-stimulatory pseudoknots from representative bat coronaviruses

Rohith Vedhthaanth Sekar, Patricia J. Oliva, Michael T. Woodside

Shadow enhancers mediate trade-offs between transcriptional noise and fidelity

Alvaro Fletcher, Zeba Wunderlich, German Enciso

The MAPK/ERK channel capacity exceeds 6 bit/hour

Paweł Nałęcz-Jawecki, Paolo Armando Gagliardi, Marek Kochańczyk, Coralie Dessauges, Olivier Pertz, Tomasz Lipniacki

Fast and versatile sequence-independent protein docking for nanomaterials design using RPXDock

William Sheffler, Erin C. Yang, Quinton Dowling, Yang Hsia, Chelsea N. Fries, Jenna Stanislaw, Mark D. Langowski, Marisa Brandys, Zhe Li, Rebecca Skotheim, Andrew J. Borst, Alena Khmelinskaia, Neil P. King, David Baker

Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data

David Augustin, Ben Lambert, Ken Wang, Antje-Christine Walz, Martin Robinson, David Gavaghan

Deep self-supervised learning for biosynthetic gene cluster detection and product classification

Carolina Rios-Martinez, Nicholas Bhattacharya, Ava P. Amini, Lorin Crawford, Kevin K. Yang

Inferring evolutionary trajectories from cross-sectional transcriptomic data to mirror lung adenocarcinoma progression

Kexin Huang, Yun Zhang, Haoran Gong, Zhengzheng Qiao, Tiangang Wang, Weiling Zhao, Liyu Huang, Xiaobo Zhou

Design of an adaptable intrafascicular electrode (AIR) for selective nerve stimulation by model-based optimization

Federico Ciotti, Andrea Cimolato, Giacomo Valle, Stanisa Raspopovic

The proportion of resistant hosts in mixtures should be biased towards the resistance with the lowest breaking cost

Pauline Clin, Frédéric Grognard, Didier Andrivon, Ludovic Mailleret, Frédéric M. Hamelin

Canonical Response Parameterization: Quantifying the structure of responses to single-pulse intracranial electrical brain stimulation

Kai J. Miller, Klaus-Robert Müller, Gabriela Ojeda Valencia, Harvey Huang, Nicholas M. Gregg, Gregory A. Worrell, Dora Hermes

Two modes of fusogenic action for influenza virus fusion peptide

Michal Michalski, Piotr Setny

Enabling interpretable machine learning for biological data with reliability scores

K. D. Ahlquist, Lauren A. Sugden, Sohini Ramachandran

Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression

Sam De Meyer, Daniel Felipe Cruz, Tom De Swaef, Peter Lootens, Jolien De Block, Kevin Bird, Heike Sprenger, Michael Van de Voorde, Stijn Hawinkel, Tom Van Hautegem, Dirk Inzé, Hilde Nelissen, Isabel Roldán-Ruiz, Steven Maere

Amino acid sequence assignment from single molecule peptide sequencing data using a two-stage classifier

Matthew Beauregard Smith, Zack Booth Simpson, Edward M. Marcotte

CRISPR-Analytics (CRISPR-A): A platform for precise analytics and simulations for gene editing

Marta Sanvicente-García, Albert García-Valiente, Socayna Jouide, Jessica Jaraba-Wallace, Eric Bautista, Marc Escobosa, Avencia Sánchez-Mejías, Marc Güell

Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection

Junya Sunagawa, Ryo Komorizono, Hyeongki Park, William S. Hart, Robin N. Thompson, Akiko Makino, Keizo Tomonaga, Shingo Iwami, Ryo Yamaguchi

Neural network and kinetic modelling of human genome replication reveal replication origin locations and strengths

Jean-Michel Arbona, Hadi Kabalane, Jeremy Barbier, Arach Goldar, Olivier Hyrien, Benjamin Audit