Bioinformatics

Genomic and transcriptomic analyses of Heteropoda venatoria reveal the expansion of P450 family for starvation resistance in spider

1. Guoqing Zhang
2. Yiru Wang
3. Hongcen Jiang
4. Yi Wang

Reviewed by GigaScience

A network regularized linear model to infer spatial expression pattern for single cell

1. Chaohao Gu
2. Hu Chen
3. Zhandong Liu

• Curated by eLife

  eLife Assessment

  The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its methodological framework remains incomplete regarding spatial communication applications and feature dependence. The approach demonstrates notable utility by enabling higher-resolution cell mapping across multiple biological systems and spatial platforms compared to existing tools.

Reviewed by eLife

Systematic discovery of directional regulatory motifs associated with human insulator sites

1. Naoki Osato
2. Michiaki Hamada

Reviewed by Review Commons

ESM-Effect: An Effective and Efficient Fine-Tuning Framework towards accurate prediction of Mutation’s Functional Effect

1. Moritz Glaser
2. Johannes Brägelmann

Reviewed by Arcadia Science

Inferring protein from mRNA concentrations using convolutional neural networks

1. Patrick Maximilian Schwehn
2. Pascal Falter-Braun

Reviewed by preLights

In Silico Toxicity Assessment of Organophosphates: A DFT and Molecular Docking Study on Their Interaction with Human Serum Albumin (HSA)

1. Tanya Singh
2. Nisha Shankhwar
3. Neeta Raj Sharma
4. Anil Kumar
5. Awadhesh Kumar Verma

Reviewed by PREreview

On estimating phenomenological model states for epileptic seizure prediction

1. A I Bhatti

Reviewed by PREreview

Benchmarking Long-read Sequencing Tools for Chromosome End-specific Telomere Analysis

1. Jake Reed
2. Mark Oelkuct
3. Kevin Coombes

Reviewed by PREreview

Identification of Potential Hub Genes and Therapeutic Targets in Colorectal Cancer Using Integrated Bioinformatics Approaches

1. Kamalakannan D
2. Manivannan R
3. Suresh Gopal Kumar
4. Dilip Kumar

Reviewed by PREreview

CompactTree: a lightweight header-only C++ library and Python wrapper for ultra-large phylogenetics

1. Niema Moshiri

• Curated by GigaByte

  Editors Assessment:

  As volumes of viral and bacterial sequence data grow exponentially, the field of computational phylogenetics now demands resources to manage the burgeoning scale of this input data. This study introduces CompactTree, a C++ library designed for ultra-large phylogenetic trees with millions of tips. To address these scalability issues while maintaining ease of incorporation into external code bases, CompactTree is a header-only library with enhanced performance utilizing minimal dependencies, optimized node representation, and memory-efficient tree structure schemes. Resulting in significantly reduced memory footprints and improved processing times. Peer review requested some more detail on the functionality and some real-world examples, demonstrating the current utility of the tool. Although primarily supporting the (text-based) Newick format, the increased and extensibility scalability holds promise for multiple biological and epidemiological applications supporting more complex formats such as Nexus and NeXML. The tool is open source (GPLv3 licensed) and available in GitHub: https://niema.net/CompactTree

  This evaluation refers to version 1 of the preprint

Reviewed by GigaByte