Pinned Repositories
AF-cryptic-pocket
Cryptic pocket prediction using AlphaFold 2
BPTI-TICA-waterdynamics
tICA to capture local loop motion. Describes how to analyse loop movement using TICA and how to run PT-Metad using TIC vectors
Classifier-CV-sampling
Binary classifier as CV in enhanced sampling
Funnel-metadynamics
This repo is designed to give initial files to perform Funnel metadynamics as described in the paper Resolving the problem of trapped water in binding cavities: prediction of host–guest binding free energies in the SAMPL5 challenge by funnel metadynamics (https://link.springer.com/article/10.1007/s10822-016-9948-6)
Important-programmes
Histogram, bootstrapping and some analyses
Infrequent-metadynamics
Prediction of transition time (kinetics) associated with aromatic ring flipping using infrequent metadynamics
PAP-review-inputs
How one can use binary classifiers, variational auto-encoder, TICA, PCA, distance and dihedral order parameters as CVs in context of pepsin-like aspartic proteases e.g. BACE1 and plasmepsin-II.
Plasmepsin-bace
This repo provides all details to repertory and validate the paper Flap dynamics in pepsin-like aspartic proteases: a computational perspective using Plasmepsin-II and BACE-1 as model systems (doi: https://doi.org/10.1101/2020.04.27.062539)
Plotting-MD-Metadynamics
Jupyter Notebook showing how to plot FES, histograms and time-series data using Matplotlib.
sklearn-sfa
This project provides Slow Feature Analysis as a scikit-learn-style package.
sbhakat's Repositories
sbhakat/Plotting-MD-Metadynamics
Jupyter Notebook showing how to plot FES, histograms and time-series data using Matplotlib.
sbhakat/PAP-review-inputs
How one can use binary classifiers, variational auto-encoder, TICA, PCA, distance and dihedral order parameters as CVs in context of pepsin-like aspartic proteases e.g. BACE1 and plasmepsin-II.
sbhakat/BPTI-TICA-waterdynamics
tICA to capture local loop motion. Describes how to analyse loop movement using TICA and how to run PT-Metad using TIC vectors
sbhakat/Funnel-metadynamics
This repo is designed to give initial files to perform Funnel metadynamics as described in the paper Resolving the problem of trapped water in binding cavities: prediction of host–guest binding free energies in the SAMPL5 challenge by funnel metadynamics (https://link.springer.com/article/10.1007/s10822-016-9948-6)
sbhakat/Play-data-MD
Repo for Play with Real Data competition https://sdat.ir/en/playdata
sbhakat/tutorials
Various tutorials about MD setup and analysis, protein-ligand docking, machine learning and lots of other interesting things.
sbhakat/MasterMSM
Python package for generating Markov state models
sbhakat/sklearn-sfa
This project provides Slow Feature Analysis as a scikit-learn-style package.
sbhakat/Time-Series-Transformer
A data preprocessing package for time series data. Design for machine learning and deep learning.
sbhakat/vmd-python
Installable VMD as a python module
sbhakat/AI-De-Novo-Molecule-Design
Deep learning AI for generating new molecules that bond to the COVID-19.
sbhakat/CompressionVAE
General-purpose dimensionality reduction and manifold learning tool based on Variational Autoencoder, implemented in TensorFlow.
sbhakat/D3-HLP-MSM-workflow
MSM workflow for: Thomas, T.; Yuriev, E; Chalmers, D. K. "MarkovState Model Analysis of Haloperidol Binding to the D3 Dopamine Receptor."
sbhakat/exposons-with-jug
Use the parallelization framework jug to build exposons!
sbhakat/getcontacts
Library for computing dynamic non-covalent contact networks in proteins throughout MD Simulation
sbhakat/GromacsWrapper
GromacsWrapper is a python package that wraps system calls to Gromacs tools into thin classes. This allows for fairly seamless integration of the gromacs tools into python scripts. This is generally superior to shell scripts because of python’s better error handling and superior data structures. It also allows for modularization and code re-use. In addition, commands, warnings and errors are logged to a file so that there exists a complete history of what has been done.
sbhakat/HK_DataMiner
sbhakat/iaf-vae
Pytorch Implementation of OpenAI's "Improved Variational Inference with Inverse Autoregressive Flow"
sbhakat/msmbuilder_codes_scripts
Analyzing large-scale MD simulations by MSM modeling and TPT analysis.
sbhakat/playground
Play with neural networks!
sbhakat/ProLIF
Protein-Ligand Interaction Fingerprints
sbhakat/PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
sbhakat/RAVE
Reweighted Autoencoded Variational Bayes for Enhanced Sampling (RAVE)
sbhakat/SICA
slow independent component analysis, SICA algorithm
sbhakat/SindyAutoencoders
sbhakat/Target2DeNovoDrug
sbhakat/transformer-time-series-prediction
proof of concept for a transformer-based time series prediction model
sbhakat/TSMD
Tree Search Molecular Dynamics Simulation
sbhakat/Variational-Lstm-Autoencoder
Lstm variational auto-encoder API for time series anomaly detection and features extraction
sbhakat/vib
Theory and PyTorch implementation of Deep Variational Information Bottleneck