Current Bioinformatics - Volume 20, Issue 3, 2025

Although enzymes have the advantage of efficient catalysis, natural enzymes lack stability in industrial environments and do not even meet the required catalytic reactions. This prompted us to urgently de novo design new enzymes. As a powerful strategy, computational method can not only explore sequence space rapidly and efficiently, but also promote the design of new enzymes suitable for specific conditions and req Read More

IntroductionIdentifying and predicting protein-coding regions within DNA sequences play a pivotal role in genomic research. This paper introduces an approach for identifying protein-coding regions in DNA sequences by employing a hybrid methodology that combines digital bandpass filtering with wavelet transform and various spectral estimation techniques to enhance exon prediction. Specifically, the Haar and Daubechies w Read More

BackgroundThe use of machine learning models in sequence-based Protein-Protein Interaction prediction typically requires the conversion of amino acid sequences into feature vectors. From the literature, two approaches have been used to achieve this transformation. These are referred to as the Independent Protein Feature (IPF) and Merged Protein Feature (MPF) extraction methods. As observed, studies have predominantly Read More

BackgroundMutations in metabolism-related genes in somatic cells potentially lead to disruption of metabolic pathways, which results in patients exhibiting different molecular and pathological features.ObjectiveIn this study, we focused on somatic mutation data to investigate the significance of metabolic mutation typing in guiding the prognosis and treatment of breast cancer patients.MethodsThe somatic mutation profile of b Read More

IntroductionVariants of concern were identified in severe acute respiratory syndrome coronavirus 2, namely Alpha, Beta, Gamma, Delta, and Omicron. This study explores the mutations of the Omicron lineage and its differences from other lineages through a protein language model.MethodsBy inputting the severe acute respiratory syndrome coronavirus 2 wild-type sequence into the protein language model e Read More

IntroductionWe present YADA, a cellular content deconvolution algorithm for estimating cell type proportions in heterogeneous cell mixtures based on gene expression data. YADA utilizes curated gene signatures of cell type-specific marker genes, either obtained intrinsically from pure cell type expression matrices or provided by the user.MethodsYADA implements an accessible and extensible deconvolution framework uniquely Read More

BackgroundCurrently, various types of peptides have broad implications for human health and disease. Some drug peptides play significant roles in sensory science, drug research, and cancer biology. The prediction and classification of peptide sequences are of significant importance to various industries. However, predicting peptide sequences through biological experiments is a time-consuming and expensive process. Moreove Read More