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<h4>Summary</h4>Phylogenetic trees are ubiquitous and central to biology, but most published trees are available only as visual diagrams and not in the machine-readable Newick format. There are, thus, thousands of published trees in the scientific …
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Read PDF<b>Background/Objectives:</b> The rapid expansion of targeted therapies has reshaped oncology by exploiting ligand-receptor interactions (LRI) to improve treatment specificity and patient outcomes. However, the data describing these ligands remain fragmented across multiple sources, limiting accessibility …
Read PDF<h4>Summary</h4>In the analysis of diverse omics data, a common and important preliminary step involves computing low-dimensional embeddings using techniques such as PCA, UMAP, t-SNE, or variational autoencoders. These embeddings provide a global overview of sample …
Read PDFHybrid simulation is essential for modeling biochemical systems that mix low-copy stochastic dynamics with high-abundance deterministic processes. We present HySimODE, a Python framework that automates hybrid simulation directly from user-defined ordinary differential equation-based models. HySimODE …
Read PDF<h4>Motivation</h4>Segmentation and automated genome annotation (SAGA) techniques, such as Segway and ChromHMM, assign labels to every part of the genome, identifying similar patterns across multiple genomic input signals. Inferring biological meaning in these patterns remains …
Read PDF<h4>Motivation</h4>DNA methylation (DNAme) is the best studied epigenetic mechanism that plays pivotal role in tissue differentiation and epigenetic disruption has been correlated to diverse disease types (e.g. cancer, metabolic disorders). While various DNAme array platforms …
Read PDF<h4>Motivation</h4>Genomic language models (gLMs) face a fundamental efficiency challenge: one must either maintain separate specialized models for each biological modality (DNA and RNA) or develop large multimodal architectures. Both approaches impose significant computational burdens-modality-specific models …
Read PDF<h4>Background and aim</h4>Despite its role in healthcare delivery and accessibility, the potential of bioinformatics to transform disease diagnosis in SSA remains unknown. This narrative review aims to assess the current status of bioinformatics initiatives in …
Read PDF<h4>Motivation</h4>Although deep learning has accelerated protein design, current protein representations such as sequences or full-atom structures scale non-linearly with protein length. We propose a sparse and interpretable representation for proteins, based on evolutionarily conserved fragments. …
Read PDF<h4>Motivation</h4>Cryogenic electron tomography (cryo-ET) enables in situ visualization of macromolecular and cellular structures from tilt-series projections. Reconstruction quality is often compromised by extremely low signal-to-noise ratio (SNR) and vignetting artifacts arising from detector truncation under …
Read PDFAI disclosure mandates have rapidly become standard in scientific publishing, a genuine success of scholarly self-governance. Yet across 10,000 bioRxiv preprints, disclosure tracks only modestly with code and data sharing. The next phase of policy …
Read PDF<h4>Motivation</h4>Early-stage drug discovery relies on testing compounds across a limited set of cell lines, making it challenging to capture biological diversity while maintaining experimental efficiency. Current predictive approaches for identifying responsive cell lines often depend …
Read PDF<h4>Motivation</h4>Large-scale bioinformatics analyses increasingly require collaboration across multiple cohorts and institutions, yet existing workflows often rely on data co-localization, which is slow, difficult to scale, and raises privacy concerns. We present a privacy-preserving federated analytics …
Read PDF<h4>Motivation</h4>Medical text classification plays a critical role in clinical decision support, automated diagnosis, and biomedical research. However, deep learning models are highly susceptible to dataset-induced biases, such as label bias and keyword bias, which can …
Read PDF<h4>Motivation</h4>Proteins change shape as they work, and these changing states control whether binding sites are exposed, signals are relayed, and catalysis proceeds. Most protein language models (PLMs) pair a sequence with a single structural snapshot, …
Read PDF<h4>Summary</h4>Recently, Anwar et al. introduced a method combining the ROTS reproducibility optimisation procedure with empirical Bayes variance estimation from limma. Here, we clarify several methodological aspects to support accurate interpretation of the results. We emphasise …
Read PDF<h4>Motivation</h4>Structure-based drug design (SBDD) aims to generate ligand molecules that tightly bind to specific protein targets, a critical step in drug discovery. Diffusion models have shown promise for this task, yet existing methods struggle to …
Read PDF<h4>Motivation</h4>Developing segmentation models that remain reliable across diverse medical imaging domains and accurately delineate complex anatomical boundaries remains a persistent challenge for clinical deployment. Variations in imaging modalities, scanners, and acquisition settings introduce significant domain …
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