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Unlabelled: In chemoinformatics and bioinformatics fields, one of the main computational challenges in various predictive modeling is to find a suitable way to effectively represent the molecules under investigation, such as small molecules, proteins and even complex interactions. To solve this problem, we developed a freely available R/Bioconductor package, called Compound-Protein Interaction with R (Rcpi), for complex molecular representation from drugs, proteins and more complex interactions, including protein-protein and compound-protein interactions. Rcpi could calculate a large number of structural and physicochemical features of proteins and peptides from amino acid sequences, molecular descriptors of small molecules from their topology and protein-protein interaction and compound-protein interaction descriptors. In addition to main functionalities, Rcpi could also provide a number of useful auxiliary utilities to facilitate the user's need. With the descriptors calculated by this package, the users could conveniently apply various statistical machine learning methods in R to solve various biological and drug research questions in computational biology and drug discovery.
Availability And Implementation: Rcpi is freely available from the Bioconductor site (http://bioconductor.org/packages/release/bioc/html/Rcpi.html).
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http://dx.doi.org/10.1093/bioinformatics/btu624 | DOI Listing |
Bioinformatics
September 2025
Institute of Medical Data Science, Otto-von-Guericke University Magdeburg, Magdeburg, 39120, Germany.
Summary: Recent advances in single-cell sequencing made it possible to not just analyze a cell's individual expression pattern, but to gain insights into a single cell's genome using the cutting-edge technology single-cell DNA sequencing. Mission Bio is, with the Tapestri platform, one of the few providers of this technology. So far, however, there is only little open-source software available for user-friendly processing and quality analysis of this data type.
View Article and Find Full Text PDFPLoS Comput Biol
August 2025
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
G-quadruplexes (G4s) are nucleic acid secondary structures with important regulatory functions. Single-nucleotide variants (SNVs), one of the most common forms of genetic variation, can potentially impact the formation of G4 structures if they occur within G4 regions. However, there is currently a lack of software tools specifically designed to assess such effects.
View Article and Find Full Text PDFInt Urol Nephrol
August 2025
Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Objectives: The critical need for minimally invasive biomarkers to stratify non-muscle-invasive (NMIBC) and muscle-invasive bladder cancer (MIBC) prompted our investigation into tumor-specific glycan signatures. We hypothesized that lectin-based glycoprofiling could stratify MIBC and NMIBC via stage-specific glycan remodeling. Leveraging the emerging role of lectin microarrays in glycoprofiling, the first comprehensive plasma-based analysis comparing NMIBC and MIBC glycosylation patterns using a high-density 95-lectin platform was conducted.
View Article and Find Full Text PDFGigaByte
June 2025
The Vision Center, Department of Surgery, and Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA.
Unlabelled: Chevreul is an open-source R Bioconductor package and interactive R Shiny app for processing and visualising single-cell RNA sequencing (scRNA-seq) data. Chevreul differs from other scRNA-seq analysis packages in its ease of use, capacity to analyze full-length RNA sequencing data for exon coverage and transcript isoform inference, and support for batch correction. Chevreul enables exploratory analyses of scRNA-seq data using Bioconductor SingleCellExperiment objects (or converted Seurat objects), including batch integration, quality control filtering, read count normalization and transformation, dimensionality reduction, clustering at a range of resolutions, and cluster marker gene identification.
View Article and Find Full Text PDFBioinform Adv
July 2025
Department of Molecular Life Sciences, University of Zurich, Zurich 8057, Switzerland.
Motivation: The Beacon v2 specification, established by the Global Alliance for Genomics and Health (GA4GH), consists of a standardized framework and data models for genomic and phenotypic data discovery. By enabling secure, federated data sharing, it fosters interoperability across genomic resources. Progenetix, a Beacon v2 reference implementation, exemplifies its potential for large-scale genomic data integration, offering open access to genomic mutation data across diverse cancer types.
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