Bioinformatics Advances

🔬 Analysis scripts, codon count tables, RSCU matrices, and CAI results are available at github.com/bicnehu/mito-t….

RSCU, ENc–GC3, and CAI profiling show mitochondrial bias is mutation-driven while nuclear codon preferences track translational selection, concentrated in core OXPHOS subunits.

🪱 New research in Bioinformatics Advances: "Synonymous but not silent: Functional codon bias reveals decoupled mitonuclear evolution in parasitic worms"  Read it here: doi.org/10.1093/bioadv…

🗂️ FetchM is available at github.com/Tasnimul-Arabi…

FetchM links NCBI Genome assemblies to BioSample contextual metadata via the Entrez API, automating retrieval of collection date, host, and geographic origin. Applied to 14,382 Vibrio cholerae genomes, it recovered temporal metadata for 89% of records and revealed persistent gaps in host annotation.

🧫 Latest research in Bioinformatics Advances: "FetchM: Streamlining genome and metadata integration for bacterial comparative genomics"  Read it here: doi.org/10.1093/bioadv…

🧬 EGGS is available at github.com/TQ-Smith/EGGS

EGGS addresses a key gap in population genetics simulation: rather than randomly distributing missing genotypes, it replicates the spatial structure of missingness from empirical data. Validated against ancient DNA, it also handles deamination, pseudohaploids, phase removal, and format conversion.

🥚New paper in Bioinformatics Advances: "EGGS: Empirical genotype generalizer for samples"  Read it here: doi.org/10.1093/bioadv…

🎂 Today marks 5 years of operation for Bioinformatics Advances! Since our launch, researchers around the world have shared their methods, tools, and findings through our pages. To every author, reviewer, and reader who has been part of that: thank you. Here's to the science still to come! 🧬💻

@StefanieDimmel1 📦 DoTools is available at:  🔹bioconductor.org/packages/relea…  🔹pypi.org/project/DoTool…   Source code can be found at:  🔹github.com/MarianoRuzJura…  🔹github.com/davidrm-bio/Do…

DoTools unifies scRNA-seq analysis across R and Python, wrapping tools like scVI, CellTypist, and CellBender into Seurat, SingleCellExperiment, and Scanpy pipelines. It covers QC, batch correction, annotation, DGE, and visualization with statistical overlays unavailable in other frameworks.

⚙️ New in Bioinformatics Advances: "DoTools: A cross platform framework to streamline common single cell workflows"  Read it here: doi.org/10.1093/bioadv… Authors include: @StefanieDimmel1

🖥️ scRANGE is available at github.com/mvrobles/scRAN…

Both were benchmarked against seven tools on five public datasets and a novel refractory epilepsy scRNA-seq dataset.

🔬 Recently published in Bioinformatics Advances: "New algorithms for unsupervised cell clustering from scRNA-seq data"  Available at  doi.org/10.1093/bioadv…

💾 GlncDDR source code and datasets are available at github.com/BioDataLearnin…

GlncDDR applies node2vec graph embeddings of TCGA pan-cancer transcriptomic data with logistic regression, random forest, and SVM classifiers to predict DDR-associated lncRNAs. Models achieved ROC-AUC ~0.93 on independent test data and identified 1,232 candidate lncRNAs.

🧬 Just published in Bioinformatics Advances: "Accurate prediction of candidate lncRNAs associated with DNA damage response based on gene expression patterns from graph neural networks"  Full text at doi.org/10.1093/bioadv…