Systems & Computational Biology
Recent approaches in computational modelling for controlling pathogen threatsRecent advances and remaining challenges in using computational approaches to model various aspects of pathogen infection and transmission are discussed and reviewed.
The importance of DNA sequence for nucleosome positioning in transcriptional regulationMachine learning on DNA sequences shows that nucleosomes are positioned by DNA sequence patterns to support the stages of transcription by directing competition between nucleosomes and transcription factors, as well as regulating RNA polymerase II dynamics.
Differential growth regulates asymmetric size partitioning in Caulobacter crescentusWe develop a quantitative model for asymmetric size partitioning in bacteria based on differential growth of daughter cell compartments.
Systems genetics analysis of human body fat distribution genes identifies adipocyte processesUsing Bayesian network analysis, we modeled gene-gene interactions and predicted novel regulators of adipose tissue fat storage. We show that five novel genes affect adipogenesis or mitochondrial function in human fat cells.
Interrogating endothelial barrier regulation by temporally resolved kinase network generationThis study introduces TREKING, a methodology for broadly interrogating kinases to elucidate time-resolved functional kinase signaling networks that drive endothelial barrier disruption and recovery.
Systemic metabolic depletion of gut microbiome undermines responsiveness to melanoma immunotherapyRelationship between gut microbiome composition and immunotherapy efficacy.
A comparative study of structural variant calling in WGS from Alzheimer’s disease familiesWe developed a flexible protocol to generate a high-quality deletion call set and a truth set of Sanger sequencing–validated deletions with precise breakpoints between 1 and 17,000 bp from whole-genome sequencing data in multiplex families with Alzheimer’s disease.
Stability of gut microbiome after COVID-19 vaccination in healthy and immuno-compromised individualsThis study highlights the resilience of the gut microbiome to host immune changes triggered by COVID-19 vaccination and suggest minimal, if any, impact on microbiome-mediated processes.
NeoMUST: an accurate and efficient multi-task learning model for neoantigen presentationNeoMUST, a multi-task learning model, efficiently predicts neoantigen presentation via MHC-I molecules, rivaling existing algorithms with significantly shorter training time. Its GitHub repository offers free access for advancing cancer immunotherapy development.
Accessory genes define species-specific routes to antibiotic resistanceIn this study, we show how decision tree models can accurately predict the AMR phenotype, and this study highlights that resistance is a result of multi-gene interactions, which are often species-specific.