rnaimehaom Goto Github PK

aqsoldb-1

AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds

aqsolpred-web

Online solubility prediction tool (streamlit) that runs the top-performing ML model (AqSolPred).

argenomic

Argenomic is an illumination algorithm for optimization of small organic molecules.

aricode

R package for computation of (adjusted) rand-index and other such scores

armchem

Tool for creating deep learning model for predicting properties of chemical compounds based on SMILES.

arpeggio

mirror of https://bitbucket.org/harryjubb/arpeggio

arpeggio-1

Calculation of interatomic interactions in molecular structures

arpeggio-2

Calculation of interatomic interactions in molecular structures

arriba

Fast and accurate gene fusion detection from RNA-Seq data

arrow

Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing

arules

Mining Association Rules and Frequent Itemsets with R

arulescba

Classification Based on Association Rules in R

asali-kila

ASALI is an open-source software for solving gas thermodynamic and transport properties, catalytic reactors and chemical equilibrium calculations.

asap

Fast and accurate Active SAmpling method for Pairwise comparisons

ase_ani

ANI-1 neural net potential with python interface (ASE)

askcos

Software package for computer aided synthesis planning

askcos-1

http://askcos.mit.edu

askcos_synthesizability

aspen

ASPEN repository, associated with 2019 publication

assessing_mol_prediction_confidence

https://arxiv.org/abs/2102.11439

ast2ast

Translates an R function into an external pointer to a C++ function. The typical use case intended by 'ast2ast' are functions describing ode-systems.

astrazeneca_adme_casestudy

Case study analysis of publicly available AstraZeneca data sets CHEMBL3301363 and CHEMBL3301365

astrochem_embedding

Language models for astrochemistry

astrochem_ml

Cheminformatics tools for astrochemistry

asuratbi

A pipeline especially built for computing several single-cell datasets

asynt-gan

Computer-assisted de novo design of natural product mimetics offers a viable strategy to reduce synthetic efforts and obtain natural-product-inspired bioactive small molecules but suffers from several limitations. Deep Learning techniques can help address these shortcomings. We propose the generation of synthetic molecule structures that optimizes the binding affinity to a target. To achieve this, we leverage on important advancements in Deep Learning. Our approach generalizes to systems beyond the source system and achieves generation of complete structures that optimize the binding to a target unseen during training. Translating the input sub-systems into the latent space permits the ability to search for similar structures and the sampling from the latent space for generation.

atligator

Analysis and design of protein-protein or protein-peptide interactions based on atlas database.

atom-path-descriptor-based-machine-learning

Paper: Fast and accurate prediction of partial charges using Atom-Path-Descriptor-based machine learning

atomic_coordinates-energy_nnps

A repo for the code developed for extracting atomic coordinates and energies to train atomic NNs and neural network potentials.

atomorder

Maps atoms from reactants to products in a reaction.