pawansit Goto Github PK

2d-pharmacophore-search

simple rdkit script

ai_curriculum

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

annotatepdf

Search and color code the text in the PDF for better readability

cats2d

rdkit_cats2d

chemprop

Chemical Property Prediction with Graph Convolutional Networks

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

cookbook

The Data Engineering Cookbook

descriptastorus

Descriptor computation(chemistry) and (optional) storage for machine learning

django-3-by-example

Django 3 by Example, published by Packt

dynophore

Dynamic phormacophore from the protein binding site

emolfrag

eMolFrag is a molecular fragmentation tool based on BRICS algorithm written in Python.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hbond-alignment

Dynamic programming based Hydrogen Bond alignemnt between two protein conformaitons

hbond-dynamics

homolwat

Program to incorporate internal water molecules to GPCR models

interactiverosetta

A wxPython graphical interface for the PyRosetta and Rosetta protein modeling suites

learning_python_5the

Learning Python 5th edition Code (Mark Lutz)

ligandanalysis

Jupyter Notebook for Chemical analysis

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

micsprogramfile

Scripts for Ploting, database management and many more

molsim

first try of github

neighborsearch

List neighboring Residues of selected Residue/Ligand in Protien Structure

pawansit.github.io

plip

Protein-Ligand Interaction Profiler - Analyze and visualize non-covalent protein-ligand interactions in PDB files according to 📝 Salentin et al. (2015), https://www.doi.org/10.1093/nar/gkv315

python-for-data-analysis

An introduction to data science using Python and Pandas with Jupyter notebooks

regiosqm

See http://dx.doi.org/10.1039/C7SC04156J for more details

reinvent

Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning

risc

rmotifx

Discovery of biological sequence motifs in R

series4_predictivemodel

Can we Predict Active Compounds in OSM Series 4?