Quantori's Projects
Pipelines to process CMS data: Medicaid and Medicare
Core Data Platform providing generic infrastructure for data hosting and processing
Toolkit for downloading and preprocessing of data provided by EPA
Miscellaneous utilities to work with geographies and geometry based on shape files.
Processing pipelines for gridMET data
Deployment Descriptors and scripts for NSAPH Data Platform
Documentation for NSAPH Data Platform
Miscellaneous utilities for NSAPH data processing pipelines included in the data platform
OOP lection #3
A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF.
This repository is dedicated to the scoring of lung diseases, where we propose a two-step workflow used for segmentation and scoring of lung diseases, including COVID-19
ThunderSTORM: a comprehensive ImageJ plugin for SMLM data analysis and super-resolution imaging
Quantori Python SDK for PerkinElmer Signals Notebook
The database contains a vast set of data on the properties of glass materials.
Docking Factory is a tool to automate molecular docking runs on an HPC cluster using the Dask framework. DockingFactory provides unified way of running molecular docking with different software backends: AutoDock Vina, Smina, Qvina2, and rDock.
Docking Factory is a tool to automate molecular docking runs on an HPC cluster using the Dask framework. DockingFactory provides unified way of running molecular docking with different software backends: AutoDock Vina, Smina, Qvina2, and rDock.
DockingInterface is a Python wrapper for open-source molecular docking programs: Autodock Vina, Smina, QVina2, and rDock.
Quick Vina 2 is a fast and accurate molecular docking tool, attained at accurately accelerating AutoDock Vina. This fork of QVina 2 adds changes that allow it to run as part of DockingFactory.
rDock is a fast and versatile Open Source docking program that can be used to dock small molecules against proteins and nucleic acids. This fork adds changes to rDock that allow it to be a part of DockingFactory.
Smina is fork of AutoDock Vina that is customized to better support scoring function development and high-performance energy minimization. smina is maintained by David Koes at the University of Pittsburgh and is not directly affiliated with the AutoDock project. This fork of Smina adds changes that allow it to run as a part of DockingFactory.
AutoDock Vina is one of the fastest and most widely used open-source docking engines. It is based on a simple scoring function and rapid gradient-optimization conformational search. It was originally designed and implemented by Dr. Oleg Trott in the Molecular Graphics Lab. This fork of Vina adds changes that allow it to be a part of DockingFactory.
Code that helps to write logic based on SIMD operations
Code that helps to write logic based on SIMD operations
Data Processing and Machine learning methods for the Open Skills Project
The implementation, training and evaluation of a Structure Seer machine learning model designed for reconstruction of adjacency of a molecular graph from the labelling of its nodes.
Study management software for lab-based research organizations
VarDict Java port
A heterogeneous OpenCL implementation of AutoDock Vina