/tools

LucaVirus is a tool designed to model the evolutionary and functional landscape of viruses using a unified genome-protein language model. It provides datasets of viral sequences and supports various tasks such as predicting protein properties and classifying viral sequences.

Grappa is a machine learned molecular mechanics force field that utilizes graph neural networks to predict bonded parameters for molecular simulations. It integrates with GROMACS and OpenMM, allowing users to parametrize systems and train custom models using various molecular datasets.

NA-MPNN is a tool for RNA sequence design and predicting protein-DNA specificity. It provides training and inference code for generating sequences and evaluating specificity, making it relevant for molecular design applications.

This tool models human 5' UTR sequences to predict their impact on translation and enables the design of new sequences for optimal protein expression. It utilizes deep learning and genetic algorithms to engineer RNA sequences, making it applicable in mRNA therapeutics and synthetic biology.

RiboDiffusion is a tool for tertiary structure-based RNA inverse folding utilizing generative diffusion models. It allows users to generate RNA sequences from given PDB structures, facilitating molecular design and exploration in RNA biology.

RiboNN is a deep learning model designed to predict translation efficiency from mRNA sequences. It allows users to train models on specific datasets and make predictions using pretrained models, focusing on the molecular aspects of RNA translation.

RNAPro is a state-of-the-art model for predicting the 3D structure of RNA molecules, developed in collaboration with experts from a Kaggle competition. It utilizes advanced techniques such as template modeling and multiple sequence alignment to enhance the accuracy of RNA structure predictions.

LLM4Mol is a repository that explores the application of large language models in molecular design and protein research. It serves as a hub for studies and techniques that leverage AI to advance understanding in molecular properties and material science.

structRFM is an open-source structure-guided RNA foundation model designed for robust structural and functional inference. It integrates sequence and structural knowledge to achieve state-of-the-art performance in RNA secondary and tertiary structure prediction, as well as function prediction tasks.

CoPRA is a tool designed for predicting protein-RNA binding affinity using pretrained sequence models. It includes datasets for training and evaluation, as well as model weights for users to implement and fine-tune their predictions.

EquiPNAS is a tool designed for predicting binding sites between proteins and nucleic acids (DNA/RNA) using equivariant deep graph neural networks. It provides methods for training and testing models specifically tailored for protein-DNA and protein-RNA interactions.

ComplexMixtures.jl is a Julia package designed to study the interactions between solutes and solvents of complex molecular shapes. It utilizes minimum-distance distribution functions to analyze these interactions, providing insights into molecular behavior in solutions.

AnnapuRNA is a scoring function that evaluates RNA-ligand complex structures generated by computational docking methods. It provides a framework for predicting the interactions between RNA and small molecules, making it useful for drug discovery and molecular design.

fpocketR is a command-line tool designed to analyze RNA structures and visualize drug-like RNA-ligand binding pockets. It provides functionalities for characterizing these pockets and supports various analysis workflows for RNA-ligand interactions.

Genos is a collection of foundation models designed for genomic sequence analysis, capable of handling long sequences and providing insights into gene elements and regulatory interactions. It supports various genomic tasks, including mutation prediction and cross-species classification, making it a valuable tool for researchers in molecular biology.

RFDpoly is a diffusion-based machine learning model that facilitates the de novo design of various polymers, including DNA, RNA, and proteins. It provides tools for generating molecular structures and optimizing their designs, making it a valuable resource in molecular biology and computational chemistry.

RNAvigate is a toolset designed for exploring and comparing chemical probing data and structure models of RNA. It offers an easy-to-use interface, particularly effective in Jupyter Notebooks, for documenting and sharing analyses related to RNA structures.

MCTS-RNA is a computational tool that solves the RNA inverse folding problem using Monte Carlo Tree Search. It allows for the design of nested and pseudoknot RNA structures while controlling the GC-content and its deviation precisely.

RSAPred is a Python implementation designed for predicting the binding affinity of RNA-small molecule interactions using machine learning techniques. It includes sample datasets for training and evaluation, making it a useful tool for researchers in the field of molecular biology and drug discovery.

CRAFT is a computational pipeline designed to predict circRNA sequences and their interactions with miRNAs and RNA-binding proteins (RBPs). It offers extensive functional enrichment analysis and graphical visualizations to help users explore regulatory networks involving circRNAs.

RNAiFold is a constraint programming algorithm that focuses on RNA inverse folding and molecular design. It allows users to specify target secondary structures and design RNA sequences that meet various constraints, optimizing for factors like free energy and sequence compatibility.

This repository contains QSAR models that quantitatively predict thermodynamic and kinetic binding parameters of small molecules to RNA structures, specifically targeting the HIV-1 TAR model system. It employs multiple linear regression and feature selection to create robust predictive models validated with experimental data.

Genome is a library designed for working with DNA, RNA, and other nucleic acids. It provides functionalities that are useful for molecular biology applications, particularly in the analysis and manipulation of genetic materials.

RiFold is a tool for RNA inverse folding that utilizes an auto-regressive model to generate RNA sequences based on structural evaluations. It incorporates evaluation metrics such as scRMSD and structure energy to assess the quality of the generated structures.