The COVID-19 pandemic led to devastating physical, psychological, and financial impacts on millions of people across the world. Amidst a rapidly evolving research landscape, the global scientific community was forced to swiftly adapt to novel working methods, including remote collaboration tools, virtual conferences, and online research platforms. Surveys of life sciences researchers have indicated that computational biologists experienced less disruption and a smoother transition to remote working than experimental biologists, due to their reduced reliance on laboratory equipment. Despite this adaptability, the sudden shift to remote work, compounded by stress and social isolation, has posed significant mental health challenges for these workers. However, remote work has also facilitated opportunities for more flexible work arrangements and increased collaboration across geographical boundaries. To investigate these impacts, we conducted surveys of computational biologists during the Intelligent Systems for Molecular Biology (ISMB) conferences in 2020 and 2021, which were held virtually due to the COVID-19 lockdowns. This study implements a thorough statistical analysis of the survey results to offer insights into the repercussions of the lockdowns on researchers and their work. Key areas of investigation include the effects of institutional support (or lack thereof), the difference in productivity compared to pre-lockdown levels, and the significance of gender in determining these impacts. Notably, a lack of institutional support with regard to mental health and finances was shown to have a significant negative effect on early-career researchers. Although limited by a small sample size, our study sets the stage for a more robust exploration of these trends in future research. Importantly, by illuminating the challenges and opportunities arising from the COVID-19 pandemic and lockdowns, our study offers hope for potential solutions supporting the well-being of early-career researchers in unprecedented circumstances.

SUMMARY: Once folded, natural protein molecules have few energetic conflicts within their polypeptide chains. Many protein structures do however contain regions where energetic conflicts remain after folding, i.e. they are highly frustrated. These regions, kept in place over evolutionary and physiological timescales, are related to several functional aspects of natural proteins such as protein-protein interactions, small ligand recognition, catalytic sites and allostery. Here, we present FrustratometeR, an R package that easily computes local energetic frustration on a personal computer or a cluster. This package facilitates large scale analysis of local frustration, point mutants and molecular dynamics (MD) trajectories, allowing straightforward integration of local frustration analysis into pipelines for protein structural analysis. AVAILABILITY AND IMPLEMENTATION: https://github.com/proteinphysiologylab/frustratometeR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: Cellular lineage trees can be derived from single-cell RNA sequencing snapshots of differentiating cells. Currently, only datasets with simple topologies are available. To test and further develop tools for lineage tree reconstruction, we need test datasets with known complex topologies. PROSSTT can simulate scRNA-seq datasets for differentiation processes with lineage trees of any desired complexity, noise level, noise model and size. PROSSTT also provides scripts to quantify the quality of predicted lineage trees. AVAILABILITY AND IMPLEMENTATION: https://github.com/soedinglab/prosstt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

This article describes the motivation, origin and evolution of the student symposia series organised by the ISCB Student Council. The meeting series started thirteen years ago in Madrid and has spread to four continents. The article concludes with the highlights of the most recent edition of annual Student Council Symposium held in conjunction with the 25th Conference on Intelligent Systems for Molecular Biology and the 16th European Conference on Computational Biology, in Prague, in July 2017.

Natural protein sequences contain a record of their history. A common constraint in a given protein family is the ability to fold to specific structures, and it has been shown possible to infer the main native ensemble by analyzing covariations in extant sequences. Still, many natural proteins that fold into the same structural topology show different stabilization energies, and these are often related to their physiological behavior. We propose a description for the energetic variation given by sequence modifications in repeat proteins, systems for which the overall problem is simplified by their inherent symmetry. We explicitly account for single amino acid and pair-wise interactions and treat higher order correlations with a single term. We show that the resulting evolutionary field can be interpreted with structural detail. We trace the variations in the energetic scores of natural proteins and relate them to their experimental characterization. The resulting energetic evolutionary field allows the prediction of the folding free energy change for several mutants, and can be used to generate synthetic sequences that are statistically indistinguishable from the natural counterparts.

UNLABELLED: INSECT is a user-friendly web server to predict the occurrence of Cis-Regulatory Modules (CRMs), which control gene expression. Here, we present a new release of INSECT which includes several new features, such as whole genome analysis, nucleosome occupancy predictions, and which provides additional links to third-party functional tools that complement user capabilities, CRM analysis and hypothesis construction. Improvements in the core implementation have led to a faster and more efficient tool. In addition, this new release introduces a new interface designed for a more integrative and dynamic user experience. AVAILABILITY AND IMPLEMENTATION: http://bioinformatics.ibioba-mpsp-conicet.gov.ar/INSECT2 CONTACT: [email protected].

Table of contents A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

BACKGROUND: The analysis of correlations of amino acid occurrences in globular domains has led to the development of statistical tools that can identify native contacts - portions of the chains that come to close distance in folded structural ensembles. Here we introduce a direct coupling analysis for repeat proteins - natural systems for which the identification of folding domains remains challenging. RESULTS: We show that the inherent translational symmetry of repeat protein sequences introduces a strong bias in the pair correlations at precisely the length scale of the repeat-unit. Equalizing for this bias in an objective way reveals true co-evolutionary signals from which local native contacts can be identified. Importantly, parameter values obtained for all other interactions are not significantly affected by the equalization. We quantify the robustness of the procedure and assign confidence levels to the interactions, identifying the minimum number of sequences needed to extract evolutionary information in several repeat protein families. CONCLUSIONS: The overall procedure can be used to reconstruct the interactions at distances larger than repeat-pairs, identifying the characteristics of the strongest couplings in each family, and can be applied to any system that appears translationally symmetric.

Ankyrin repeat containing proteins are one of the most abundant solenoid folds. Usually implicated in specific protein-protein interactions, these proteins are readily amenable for design, with promising biotechnological and biomedical applications. Studying repeat protein families presents technical challenges due to the high sequence divergence among the repeating units. We developed and applied a systematic method to consistently identify and annotate the structural repetitions over the members of the complete Ankyrin Repeat Protein Family, with increased sensitivity over previous studies. We statistically characterized the number of repeats, the folding of the repeat-arrays, their structural variations, insertions and deletions. An energetic analysis of the local frustration patterns reveal the basic features underlying fold stability and its relation to the functional binding regions. We found a strong linear correlation between the conservation of the energetic features in the repeat arrays and their sequence variations, and discuss new insights into the organization and function of these ubiquitous proteins.

Success is the result of planning, hard work, determination, foresight, and a little bit of luck. Unfortunately, nobody has thought to pave the road to success. Although failure can be discouraging and time-consuming, it presents incredible learning opportunities-the biggest difference between those who succeed and those who abandon their projects lies in their response to adversity. This article reviews events undertaken by the Regional Student Groups (RSGs) in India and Argentina, the problems they encountered, and what can be learned from them. RSG-India attempted to organize an online scientific meeting (also known as a virtual conference) with geographically dispersed stakeholders, a totally new concept for them. RSG-Argentina tackled the challenge of organizing a two-day symposium, their first event ever. Some of the complications they faced were easy to fix, others led to the cancellation of activities, and all of them resulted in valuable lessons. The main goal of this article is to highlight, through their experiences, the universal importance of a healthy panel of contingency plans.

MOTIVATION: Transcriptional regulation occurs through the concerted actions of multiple transcription factors (TFs) that bind cooperatively to cis-regulatory modules (CRMs) of genes. These CRMs usually contain a variable number of transcription factor-binding sites (TFBSs) involved in related cellular and physiological processes. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has been effective in detecting TFBSs and nucleosome location to identify potential CRMs in genome-wide studies. Although several attempts were previously reported to predict the potential binding of TFs at TFBSs within CRMs by comparing different ChIP-seq data, these have been hampered by excessive background, usually emerging as a consequence of experimental conditions. To understand these complex regulatory circuits, it would be helpful to have reliable and updated user-friendly tools to assist in the identification of TFBSs and CRMs for gene(s) of interest. RESULTS: Here we present INSECT (IN-silico SEarch for Co-occurring Transcription factors), a novel web server for identifying potential TFBSs and CRMs in gene sequences. By combining several strategies, INSECT provides flexible analysis of multiple co-occurring TFBSs, by applying differing search schemes and restriction parameters. availability and implementation: INSECT is freely available as a web server at http://bioinformatics.ibioba-mpsp-conicet.gov.ar/INSECT .