Unit of Research on Computational Biology and Drug Design. Mexico Children's Hospital Federico G贸mez. (@uibcdf)
  • Stars
    star
    119
  • Global Org. Rank 52,497 (Top 17 %)
  • Registered almost 7 years ago
  • Most used languages
    Python
    51.6 %
    HTML
    6.5 %
    Rich Text Format
    3.2 %
  • Location 馃嚥馃嚱 Mexico
  • Country Total Rank 440
  • Country Ranking
    Rich Text Format
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    Python
    72
    HTML
    192

Top repositories

1

OpenPharmacophore

An open library to work with pharmacophores.
Python
29
star
2

action-sphinx-docs-to-gh-pages

GitHub Action: The sphinx documentation in a repository is compiled and deployed to GitHub Pages through the gh-pages branch.
13
star
3

action-build-and-upload-conda-packages

GitHub Action: new conda packages are built and uploaded to Anaconda when a new released or pre-released version is declared.
11
star
4

MolSysMT

Open source library to work with molecular systems
Python
11
star
5

PyPharmer

Python API for Pharmer
HTML
9
star
6

Academia

Este repositorio debe ser el punto de partida y encuentro para cualquier investigador o estudiante que quiera comenzar a trabajar con/en la UIBCDF. Si has ca铆do aqu铆 por otro motivo y este material te es 煤til, eres m谩s que bienvenido a usarlo e interaccionar con nosotros.
Jupyter Notebook
6
star
7

action-html-dir-to-gh-pages

GitHub Action: The gh-pages branch is updated with the content of an html directory to be deployed to GitHub Pages.
3
star
8

BiFrEE

First steps of an open library to estimate binding free energies with the MM/GBSA approach and OpenMM.
Python
3
star
9

OpenENM

Open source library to work with elastic network models
Python
3
star
10

OpenPocket

Jupyter Notebook
2
star
11

Sabueso

Python
2
star
12

Study_Group_Pharmacophores

Pharmacophores Study Group
2
star
13

PyUnitWizard

Assistant to work with physical quantities, units, and python libraries such as Pint, openmm.unit or unyt.
Python
2
star
14

OpenPocket_old

Open Source Library to detect pockets and cavities of proteins
Jupyter Notebook
2
star
15

Taller-Python

Taller de introducci贸n a la programaci贸n en Python
Jupyter Notebook
2
star
16

Pynterpred_old

Python Interface Prediction
Python
1
star
17

Taller-Linux

Introducci贸n al uso y administraci贸n del sistemas operativos tipo Linux para el laboratorio de investigaci贸n cient铆fica.
Python
1
star
18

REMD_testbed

Replica Exchange Testbed
Jupyter Notebook
1
star
19

OpenMM-Reporters

OpenMM reporters implemented by the UIBCDF
Python
1
star
20

Study_Group_MMGBSA

MMGBSA Study Group
1
star
21

OpenInterface

Caracterizaci贸n de interfaces...
Jupyter Notebook
1
star
22

LinDelInt

Linear Delaunay Interpolator
Jupyter Notebook
1
star
23

Clustering

Clustering methods introduction and comparison
Jupyter Notebook
1
star
24

UIBCDF-Standard-Library

Methods with algorithms, tools and shortcuts usually used in the UIBCDF libraries
Python
1
star
25

OpenCTN-Tools

OpenCTN Tools
Jupyter Notebook
1
star
26

KinNetMT

Kinetic transitions networks or Conformational Markov Networks.
Python
1
star
27

DeCAF

Fork from DeCAF by Marta Stepniewska-Dziubinska. https://bitbucket.org/marta-sd/decaf
HTML
1
star
28

GPCRaptor

Tentative seed of an open library to centralize the analysis observables and tools to characterize the structure and dynamics of GPCR proteins. Valid for all-atom and coarse-grained molecular models.
Python
1
star
29

Study_Group_ENM

Elastic Network Models Study Group
1
star
30

Sabueso_old

Python
1
star
31

OpenPocket-Tools

Tests to work with OpenPocket
Jupyter Notebook
1
star
32

EBNA1

First attempt Protein Protein binding energye
Jupyter Notebook
1
star
33

OpenPharmacophore-Tools

OpenPharmacophore Benchmarks
Jupyter Notebook
1
star
34

Developer-Guidelines

Guidelines for developers of Python scientific libraries, GitHub Actions, and other open-source software at the UIBCDF.
Python
1
star
35

OMembrane

Open source library to work with membranes
Rich Text Format
1
star
36

Molecular-Systems

UIBCDF test systems
Python
1
star
37

Evidence

Scientific Python libraries or scripts often work with data coming from a database, a scientific communication, or any other external source. These data, or "evidences", are then supported by external references. Wouldn't be useful to work with "evidences" in your code?
Python
1
star