software / tool

AlphaBridge: tools for the analysis of predicted biomolecular complexes

AlphaBridge evaluates predicted biomolecular complexes using AlphaFold3 confidence metrics, clustering sequence motifs, and visualizing interfaces with 2D diagrams and interactive tools.

BRAINCELL modelling platform for stochastic nanoscale organisation and dynamic extracellular signalling among neurons and glia

NEURON-based platform that stochastically adds dendritic spines, astrocyte nanoprocesses and a dynamic extracellular space; example simulations show spines widen input-output range and myelin Kir4.1 sustains high-frequency conduction.

Pro-GAT: Reconnecting Fragmented PROTACs Using Graph Attention Transformer

Pro-GAT repairs chemically disconnected PROTAC candidates generated by diffusion models, improving validity while maintaining uniqueness.

AssayBLAST v2: Major update improving reliability and reporting of the in silico analysis of molecular multi-parameter assays

AssayBLAST v2 improves the reliability and reporting of in silico analysis for molecular multi-parameter assays through enhanced validation and computational performance.

Soil Microbial and Biochemical Properties under Conservation Agriculture in rice-based cropping systems in lower Indo-Gangetic Plain of West Bengal

Genomic Language Model for Predicting Enhancers and Their Allele-Specific Activity in the Human Genome

The paper develops DNABERT-Enhancer, a genomic language model for enhancer prediction, achieving high accuracy and identifying allele-specific activity and candidate SNPs.

The Metabarcoding Analysis Pipeline (MAP): Simple, accurate, and flexible metabarcoding

The paper introduces MAP, a metabarcoding pipeline that handles long-read data and provides accurate biodiversity estimates, outperforming existing platforms for COI metabarcoding.

Prioritizing peptides for targeted mass spectrometry experiments using deep learning

Bromo, a pairwise transformer, ranks a protein's peptide precursors by expected mass spectrometry response, beating XGBoost, PREGO and PeptideRanger on held-out yeast data, and can be fine-tuned per instrument.

Predicting cellular responses to perturbation across diverse contexts with STATE

State, a set-based transformer trained on over 100 million perturbed cells, predicts perturbation responses in new cellular contexts better than mean, linear and deep learning baselines.

RAPID: an interactive R/Shiny platform for end-to-end 16S rRNA and ITS amplicon sequence analysis using DADA2

RAPID provides interactive R/Shiny tools for end-to-end 16S rRNA and ITS amplicon analysis using DADA2, simplifying workflow execution for non-computational researchers.

Inhibited oligodendrogenesis, but not repeated mild traumatic brain injury, impairs attention in adult mice

This study shows that impaired oligodendrogenesis, not repeated mild traumatic brain injury, impairs attention in adult mice using a 5-CSRT task.

UstiGate: A standardized modular cloning platform for advanced engineering of the fungal chassis Ustilago maydis

The paper introduces UstiGate, a modular cloning platform for engineering Ustilago maydis, enabling multigene integration and standardized genetic parts.

HiCPotts: An R/Bioconductor package to identify significant interactions in chromosome conformation capture data and model sources of biases.

HiCPotts is an R/Bioconductor package that identifies significant chromatin interactions in Hi-C data while modeling biases using a zero-inflated Negative Binomial distribution.

GlyComboCLI enables command line-based FAIR workflows for glycan composition assignment in mass spectrometry data

GlyComboCLI assigns glycan compositions to mass spectrometry data through a command-line interface, supporting diverse parameters and integration into FAIR workflows.

ICONIC: An R Package for Integrating Instrumental Variable- and Negative-Control-Informed Causal Discovery and Diagnostics in Multiomic Studies

ICONIC is an R package that integrates instrumental variable and negative-control methods for causal inference in multi-omic studies, offering diagnostics and benchmarks for mediation analysis.

ABAG-Rank: Improving Model Selection of AlphaFold Antibody-Antigen Complexes by Learning to Rank

ABAG-Rank improves model selection for AlphaFold3-predicted antibody-antigen complexes by learning to rank structural ensembles using geometric descriptors and confidence scores.

seqproc: An efficient, flexible, and concise tool for sequence geometry description and transformation

seqproc is a tool that efficiently compiles sequence-geometry descriptions into execution graphs, outperforming existing tools in speed and memory usage for single-cell RNA-sequencing protocols.

Gradient-based Optimization for mRNA Sequence Design

The paper introduces ID3, a framework for optimizing mRNA sequences using gradient-based methods, balancing multiple properties while preserving amino acid sequences.

Synaptic-state-dependent plasticity routes learning signals in recurrent circuits

The paper introduces a plasticity-switching recurrent neural network (psRNN) that models synaptic state-dependent plasticity and shows it improves learning efficiency in cognitive tasks.

FlexiTAC enables controllable PROTAC linker generation across diverse structural settings using a Bayesian flow network with posterior guidance

FlexiTAC generates controllable PROTAC linkers using a Bayesian flow network, improving validity and pose quality over existing methods.

One-Class Bioacoustic Detector for Monitoring the Critically Endangered Pied Tamarin (Saguinus bicolor)

Band-pass-filtered Perch embeddings scored by a One-Class SVM trained on 82 pied tamarin calls detect the species cross-site with precision 0.86 but limited sensitivity.

Evidence-constrained mechanistic synthesis for pre-calibration perturbation inference

This paper introduces ECMS, a pre-calibration framework that uses mechanistic synthesis to evaluate biomedical evidence before full calibration, demonstrating its ability to handle heterogeneous data and preserve falsifiability.

OmicsFM brings proteomics into the foundation model era

OmicsFM is a proteomics foundation model that matches transcriptomic models in performance, revealing complementary biology between proteomics and transcriptomics.

FigTreeKit: A Python toolkit for programmatic FigTree styling, taxonomy-aware clade auditing, and phylogenetic tree rendering

FigTreeKit provides a Python toolkit for programmatically styling and auditing phylogenetic trees, with scalability testing on large bacterial and archaeal datasets.

EASI-PASS: An accessible pipeline for linking functional imaging and mRNA profiling

Matching cell masks between two-photon calcium images and thick, expanded EASI-FISH volumes recovers molecular identity for 72% (slice) to 83% (in vivo) of imaged neurons on conventional microscopes.

RhabdoForge: A Modular, Biophysically-Grounded Rendering Framework for Insect Vision Neuroethology

RhabdoForge provides a rendering framework for insect vision neuroethology, enabling simulation of compound eye dynamics and closed-loop visual behaviors.

Introducing entropy-based metrics for quantifying edge- and macro-shape complexity in leaves and beyond

This paper introduces entropy-based metrics to quantify leaf edge and macro-shape complexity, showing improved performance in predicting chemical traits and aligning with human perception.

NeuroFLAME: A Scalable, Privacy-Preserving Federated Framework for Secure, Reproducible, and Multi-Site Neuroimaging Analysis

NeuroFLAME provides a secure, scalable federated platform for multi-site neuroimaging analysis, achieving consistency with centralized methods while preserving data privacy and enabling institutional compliance.

Ambiguity of protein abbreviation PDK1: Error categorization and propagation analysis

The paper identifies and analyzes errors caused by the ambiguous abbreviation PDK1 in biomedical literature and proposes solutions to mitigate its misuse.

GDA-Pred: Generative AI-Driven Data Augmentation for Improved Prediction of IL-6 and IL-13 Inducing Peptides

GDA-Pred improves prediction of IL-6 and IL-13 inducing peptides by using generative AI to augment small datasets, enhancing classifier performance through data expansion.