Knowledge Base Resources
Contributed by cyberinfrastructure professionals (researchers, research computing facilitators, research software engineers and HPC system administrators), these resources are shared through the ConnectCI community platform. Add resources you find helpful!
DeepChem
0
DeepChem is an open-source library built on TensorFlow and PyTorch. It is helpful in applying machine learning algorithms to molecular data.
MATLAB bioinformatics toolbox
0
Bioinformatics Toolbox provides algorithms and apps for Next Generation Sequencing (NGS), microarray analysis, mass spectrometry, and gene ontology. Using toolbox functions, you can read genomic and proteomic data from standard file formats such as SAM, FASTA, CEL, and CDF, as well as from online databases such as the NCBI Gene Expression Omnibus and GenBank.
Data Visualization Tools for Julia
0
Plots.jl is the most widely used plotting library for the Julia programming language. It's known for being especially powerful in its versatility and intuitiveness. It's limited set of dependencies and wide applicability across different graphics packages make it especially helpful in visualizing the results of your latest Julia implementation.
However, there are still multiple options available for Julia programmers to visualize their datasets. The second link details a comparison against a variety of Julia packages.
Beautiful Soup - Simple Python Web Scraping
0
This package lets you easily scrape websites and extract information based on html tags and various other metadata found in the page. It can be useful for large-scale web analysis and other tasks requiring automated data gathering.
Electric field analyses for molecular simulations
0
Tool to compute electric fields from molecular simulations
AI powered VsCode Editor
0
**Cursor: The AI-Powered Code Editor**
Cursor is a cutting-edge, AI-first code editor designed to revolutionize the way developers write, debug, and understand code. Built upon the premise of pair-programming with artificial intelligence, Cursor harnesses the capabilities of advanced AI models to offer real-time coding assistance, bug detection, and code generation.
**How Cursor Benefits High-Performance Computing (HPC) Work:**
1. **Efficient Code Development:** With AI-assisted code generation, researchers and developers in the HPC realm can quickly write optimized code for simulations, data processing, or modeling tasks, reducing the time to deployment.
2. **Debugging Assistance:** Handling complex datasets and simulations often lead to intricate bugs. Cursor's capability to automatically investigate errors and determine root causes can save crucial time in the HPC workflow.
3. **Tailored Code Suggestions:** Cursor's AI provides context-specific code suggestions by understanding the entire codebase. For HPC applications where performance is paramount, this means receiving recommendations that align with optimization goals.
4. **Improved Code Quality:** With AI-driven bug scanning and linter checks, Cursor ensures that HPC codes are not only fast but also robust and free of common errors.
5. **Easy Integration:** Being a fork of VSCode, Cursor allows seamless migration, ensuring that developers working in HPC can swiftly integrate their existing VSCode setups and extensions.
In essence, for HPC tasks that demand speed, precision, and robustness, Cursor acts as an invaluable co-pilot, guiding developers towards efficient and optimized coding solutions.
It is free if you provide your own OPEN AI API KEY.
Scikit-Learn: Easy Machine Learning and Modeling
0
Scikit-learn is free software machine learning library for Python. It has a variety of features you can use on data, from linear regression classifiers to xg-boost and random forests. It is very useful when you want to analyze small parts of data quickly.
marimo | a next generation python notebook
0
Introduction seminar for new reactive python notebook from marimo ambassador.
Use Windows Subsystem for Linux for HPC Command Line Access from Windows
0
Windows Subsystem for Linux (WSL) provides a Linux environment for Windows users to access HPC resources fast and efficiently.
Conda
0
Conda is a popular package management system. This tutorial introduces you to Conda and walks you through managing Python, your environment, and packages.
Numpy - a Python Library
0
Numpy is a python package that leverages types and compiled C code to make many math operations in Python efficient. It is especially useful for matrix manipulation and operations.
How to Get the Most Out of a Mentoring Relationship by The Plank Center
0
Backed by collegiate white papers, top industry professionals, and researchers, The Plank Center’s Mentorship Guide offers basic tips and tricks on how to get the most out of a mentorship relationship. This easy-to-follow guide supplements mentorship programs, lesson plans, and professional relationships.
MDAnalysis - Python library for the analysis of molecular dynamics simulations
0
MDAnalysis is a python based library of tools for the analysis of molecular dynamics simulations. It is able to read and write many popular simulation formats including CHARMM, LAMMPS, GROMACS, and AMBER and more. This link contains the documentation pages of all MDAnalysis functions and has links to tutorials using Jupyter Notebooks.
MATLAB with other Programming Languages
0
MATLAB is a really useful tool for data analysis among other computational work. This tutorial takes you through using MATLAB with other programming languages including C, C++, Fortran, Java, and Python.
OnShape Documentation
0
This contains documentation for getting started with using OnShape for CAD. OnShape cloud-hosted CAD software that lets you work with others like on a Google Doc, with the power and capabilities of any other software like Solidworks or Inventor.
ACCESS Resource Advisor
0
A web-based tool to help researchers identify appropriate ACCESS resources for their project.