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pgclc_methylome

Data and scripts for NGS v2

pharmaceuticai

An iterative process that uses two machine learning models to generate the best inhibitors for a target protein to help reduce the time and cost of the drug discovery process

pharmacodb

Search across publicly available datasets to find instances where a drug or cell line of interest has been profiled.

pharmacokinetic_prediction

Prediction of intravenous pharmacokinetic parameters, including fu, MRT, t1/2, VD and CL, by training on 1352 compounds.

pharmadata

pharmd

MD pharmacophores and virtual screening

pharmer

🌾 Kubernetes Cluster Manager for Kubeadm (Technical Preview)

pharos-to-pdb

Mapping Pharos Targets to PDB IDs

pharos_data

Mining data from Pharos

phc-gnn

Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert

phosphoproteome_prediction

pidginv3

Protein target prediction using random forests and reliability-density neighbourhood analysis

pinet

pipelines

Containerised components for cheminformatics and computational chemistry

pipgcn

Protein Interface Prediction using Graph Convolutional Networks

pk-sim

PK-Sim® is a comprehensive software tool for whole-body physiologically based pharmacokinetic modeling

pk_predict

Predict small molecules's clearance, half-life, distribution of volume and mean residence time.

pkdb

Pharmacokinetics database

pkmodeling

Slicer Extension providing pharmacokinetic modeling

playground

plip

Protein-Ligand Interaction Profiler - Analyze and visualize non-covalent protein-ligand interactions in PDB files

pmapper

3D pharmacophore signatures and fingerprints

pmodel

Protein/Peptide conformational modeling with full atomic simulations

pointcontrast

Code for paper <PointContrast: Unsupervised Pretraining for 3D Point Cloud Understanding>

polypharmacology-db

This app enables exploration of the Drug-Target Explorer database.

postgresql_rdkit

Docker image for a Postgresql database including rdkit and the rdkit-pgsql-cartridge.

ppis-xgboost

Prediction of protein-protein interaction sites through eXtreme gradient boosting with kernel principal component analysis

pre-training-mol

Applying self pre-training method to GNN for quantum chemistry

predicting-adverse-drug-reactions-with-machine-learning

The objective of this work is to develop machine learning (ML) methods that can accurately predict adverse drug reactions (ADRs) using the databases SIDER and OFFSIDES.

predicting_molecular_activity

Drug Discovery: Predicting Molecular Activity with Deep Learning