Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data.
Graph visualization is a way of representing structural information as diagrams of abstract graphs and networks.
This page contains a list of modules available on Lmod, including modules available on the GPU accelerated nodes.
The LLVM Core libraries are well documented, and it is particularly easy to invent your own language (or port an existing compiler) to use LLVM as an optimizer and code generator.
Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.
ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations.
It allows you to align sequences using a many alignment models, using either exhaustive dynamic programming, or a variety of heuristics.
As a library, it presents a single abstract data model to the calling application for all supported formats.
The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance.
Engine2018b (Py2)2018b (Py3)The MATLAB Engine API for Python provides a package for Python to call MATLAB as a computational engine.
BerkeleyGW Package is a set of computer codes that calculates the quasiparticle properties and the optical responses of a large variety of materials from bulk periodic crystals to nanostructures such as slabs, wires and molecules.
Versatile media player which can cover various types of container format such as VCD, DVD, AVI, WMV among others.
Platform, Standard Edition (Java SE) lets you develop and deploy Java applications on desktops and servers.
Amber17 (Py2)Amber (originally Assisted Model Building with Energy Refinement) is software for performing molecular dynamics and structure prediction.
It has important applications in networking, bioinformatics, software engineering, database and web design, machine learning, and in visual interfaces for other technical domains.
Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.
Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions.
Its areas of application include high energy, nuclear and accelerator physics, as well as studies in medical and space science.
ROOT system provides a set of OO frameworks with all the functionality needed to handle and analyze large amounts of data in a very efficient way.
Wheeler Aligner (BWA) is an efficient program that aligns relatively short nucleotide sequences against a long reference sequence such as the human genome.
It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.
Math Kernel Library is a library of highly optimized, extensively threaded math routines for science, engineering, and financial applications that require maximum performance.
Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies.
BEDTools utilities allow one to address common genomics tasks such as finding feature overlaps and computing coverage.
HDF5 is a versatile, mature scientific software library designed for the fast, flexible storage of enormous amounts of data.
It is a distributed collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics.
It is fully ACID compliant, has full support for foreign keys, joins, views, triggers, and stored procedures (in multiple languages).
Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors.
Pplacer is designed to be fast, to give useful information about uncertainty, and to offer advanced visualization and downstream analysis.
OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products.
