In Arabidopsis, exposure to microbial volatile compounds promotes thiol reduction of the Cys95 residue of the photosynthetic enzyme fructose-1,6-bisphosphatase (cFBP1). Although highly conserved in plants, the Cys95 function still remains unknown. We...
International journal of molecular sciences
Jun 6, 2024
Enzymes play a crucial role in various industrial production and pharmaceutical developments, serving as catalysts for numerous biochemical reactions. Determining the optimal catalytic temperature () of enzymes is crucial for optimizing reaction cond...
Despite extensive efforts to generate and analyze reference genomes, genetic models to predict gene regulation and cell fate decisions are lacking for most species. Here, we generated whole-body single-cell transcriptomic landscapes of zebrafish, Dro...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2021
RNA-binding proteins (RBPs) have a significant role in various regulatory tasks. However, the mechanism by which RBPs identify the subsequence target RNAs is still not clear. In recent years, several machine and deep learning-based computational mode...
Tape measure (TM) proteins are essential for the formation of long-tailed phages. TM protein assembly into tails requires the action of tail assembly chaperones (TACs). TACs (e.g. gpG and gpT of E. coli phage lambda) are usually produced in a short (...
We have developed the program TwinCons, to detect noisy signals of deep ancestry of proteins or nucleic acids. As input, the program uses a composite alignment containing pre-defined groups, and mathematically determines a 'cost' of transforming one ...
Aging is universal, yet characterizing the molecular changes that occur in aging which lead to an increased risk for neurological disease remains a challenging problem. Aging affects the prefrontal cortex (PFC), which governs executive function, lear...
Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are lim...
A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features de...
Knowledge management tools that assist in systematic review and exploration of scientific knowledge generally are of obvious potential importance in evidence based medicine in general, but also to the design of therapeutics based on the protein subse...
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