Code Repository

GROMACS

GROMACS is a toolkit to perform molecular dynamics simulations of biomolecules using Newton’s equations of motion. According to the Stanford 2018 HPC update, it is the world’s most widely open source HPC application accounting for 5% of worldwide supercomputing resources, and according to the NVIDIA-commissioned Intersect360 survey it ranks #1 across all fields (academic and commercial) for GPU computing applications, and has over 40,000 citations.

http://www.gromacs.org

Uncertainty Quantification (UQ) and Sensitivity Analysis (SA)

The code distributed in this repository implements the methodology presented in the paper “Uncertainty quantification, propagation and characterization by Bayesian analysis combined with global sensitivity analysis applied to dynamical intracellular pathway models” by Eriksson & Jauhiainen et al (2018). The code is distributed under the GNU General Public License v3.0.

https://github.com/alexjau/uqsa

VeloxChem

VeloxChem is an open-source program for the calculation of electronic real and complex linear response functions at the levels of Hartree–Fock and Kohn–Sham density functional theory. With an object-oriented program structure written in a Python/C++ layered fashion, VeloxChem enables time-efficient prototyping of novel scientific approaches without sacrificing computational efficiency, so that molecular systems involving up to and beyond 500 second-row atoms (or some 10,000 contracted and in part diffuse Gaussian basis functions) can be routinely addressed. In addition, VeloxChem is equipped with a polarizable embedding scheme for the treatment of the classical electrostatic interactions with an environment that in turn is modeled by atomic site charges and polarizabilities.

The underlying hybrid MPI/OpenMP parallelization scheme makes VeloxChem suitable for execution in high-performance computing (HPC) cluster environments, showing even slightly beyond linear scaling for the Fock matrix construction with use of up to 20,000 CPU cores. An efficient—with respect to convergence rate and overall computational cost—multi-frequency/gradient complex linear response equation solver enables calculations not only of conventional spectra, such as visible/UV/X-ray electronic absorption and circular dichroism spectra, but also time-resolved linear response signals as due to ultra-short weak laser pulses. VeloxChem is distributed under the GNU Lesser General Public Licence version 2.1 (LGPLv2.1) licence and made available for download from the homepage https://veloxchem.org.

NEP-PACK: Nonlinear eigenvalue problem algorithms package

NEP-PACK is a novel open-source Julia language library for the solution of nonlinear eigenvalue problems (NEPs). The package provides a framework to represent NEPs, as well as efficient implementations of many state-of-the-art linear algebra algorithms for nonlinear eigenvalue problems, including many important algorithm classes such as Krylov methods, preconditioning methods, contour integral methods, deflation methods and Jacobi-Davidson methods. The package is designed for high-performance computing users and application researchers as well as algorithm developers. The data structures are designed with applications and algorithms in mind such that a large range of efficient solvers can be used for a wide range of problems, including problems not only defined in Julia, but also MATLAB, Python, Fortran and C. Tutorials and examples illustrate how to use the package to solve problems arising in many settings and fields, e.g., quantum physics, nanophotonics, fluid mechanics, etc.

https://github.com/nep-pack/NonlinearEigenproblems.jl

UppASD

The UppASD package is a simulation tool for atomistic spin dynamics at finite temperatures. The program evolves in time the equations of motion for atomic magnetic moments in a solid. The equations take the form of the Landau-Lifshitz-Gilbert (LLG) equation. For most of the applications done so far, the magnetic exchange parameters of a classical Heisenberg Hamiltonian have been used in ASD simulations. The parameters are extracted from ab-initio DFT codes.
Within the SeRC activities, the focus is to develop a combined spin-dynamics and molecular dynamics tool within UppASD.

https://physics.uu.se/forskning/materialteori/pagaende-forskning/uppasd/

climt

climt is a toolkit for building Earth system models in Python. climt stands for Climate Modelling and Diagnostics Toolkit — it is meant both for creating models and for generating diagnostics (radiative fluxes for an atmospheric column, for example).

https://github.com/CliMT/climt

RELION

RELION is a code used for the refinement of macromolecular structures from single-particle cryo-electron microscopy data, and with the recent revolution in terms of high resolution cryo-EM, it has become a central tool in structural biology with several thousand citations. The code is developed as a collaboration between MRC-LMB and Science for Life Laboratory.

Example reference: Kimanius, D., Forsberg, BO., Scheres, SHW., Lindahl, E. (2016) Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2. eLife 5, e18722.

https://www3.mrc-lmb.cam.ac.uk/relion/index.php

GraphQA

The opensource project concerns protein model quality assessment as part of the Data Science MCP. It consists of feature extraction, training and evaluation. The method is based on a deep learning technique called Graph Convolutional Networks (GCN) that can operate on graphs as input. As such, proteins are represented as graphs with hand-designed and/or learned features for both nodes (amino-acides) and edges (chemical and/or 3D location relations). The model is trained using local and global loss functuons based on native protein models. The method has also entered the CASP14 challenge on protein model accuracy.

Refference paper: Baldassarre et al. “GraphQA: Protein Model Quality Assessment using Graph Convolutional Networks”, Bioinformatics 2020 (https://doi.org/10.1093/bioinformatics/btaa714)

GitHub Link: https://github.com/baldassarreFe/graphqa

Server Link: http://isengard.csc.kth.se:8585/

The MISU MIT Cloud and Aerosol (MIMICA) model

MIMICA is a large-eddy simulation code designed to study cloudy planetary boundary layers (Savre et al., 2014). The model solves the non-hydrostatic anelastic equations using high-order low-dissipative numerical schemes for the advection of scalars and momentum. MIMICA contains a two-moment bulk microphysics scheme representing five types of hydrometeors including ice crystals and snow. In addition, an aerosol module can be dynamically
coupled to the solver providing the possibility for a detailed representation of cloud-aerosol feedbacks. The model has been used for numerous studies of sub-tropical and Arctic clouds. It is currently also being developed and used for deep convective cloud studies.

Reference paper: Savre J., A. M. L. Ekman, and G. Svensson (2014), Technical note: Introduction to MIMICA, a large-eddy simulation solver for cloudy planetary boundary layers, J. Adv. Model. Earth Syst., 6, doi:10.1002/2013MS000292.

https://bitbucket.org/matthiasbrakebusch/mimicav5/src/master/ (requires permission which can be obtained by contacting matthias.brakebush@aces.su.se)

OpenSpace

OpenSpace is an open-source astrovisualization tool that aims at bridging the gap between the domain scientists and the general public to portray our efforts in exploring the cosmos and showing these efforts in their proper context. OpenSpace runs on standard computer hardware and dome planetariums and also can be used by scientists in their data analysis which makes it possible to increase public outreach opportunities. In addition, OpenSpace enables simultaneous connections across the globe creating opportunity for shared experiences among audiences worldwide. OpenSpace is open source, non-commercial, and freely available software that is enabled through the generous support from the Swedish e-Science Research Centre, NASA, and the Knut and Alice Wallenberg Foundation. The project stems from the same academic collaboration between Sweden’s Linköping University (LiU) and the American Museum of Natural History (AMNH).

https://openspaceproject.com

https://github.com/OpenSpace/OpenSpace

Web-server for TOPCONS2

This is the web-server implementation of the TOPCONS2 workflow. The web-server is developed with Django 2.2.7+ and Python 3.6+. This software is open source and licensed under the MIT license.

TOPCONS2 is an updated version of the widely used TOPCONS for predicting membrane protein topologies using consensus prediction. It is faster yet more accurate than the old TOPCONS according to our solid benchmarking. Moreover, it predicts not only the trans-membrane helices, but also the location of signal peptide

This implementation employs two queuing schemes for small jobs and large jobs respectively. For single-sequence jobs submitted via web-page, they will be run directly (and usually immediately after submission) at the front-end server. For multiple-sequence jobs or jobs submitted via the API (a Python script for the command-line use of the API is included in the package), they will be forwarded to the remote servers via the WSDL (Web Service Definition Language) service. Consequently, the web-server can handle jobs of all proteins from a proteome. This implementation is suitable as as a base platform for bioinformatic prediction tools that need to be run for one or many sequences but the computational time for each sequence is short.

https://github.com/ElofssonLab/web_topcons2

Microsimulation and Prostata (R packages)

microsimulation is an R package for discrete event simulation in R and C++. It includes facilities for common random numbers and in-simulation reporting, particularly for health economic evaluations. The prostata package extends the microsimulation package to model for prostate cancer screening. The prostata package has been well validated for Sweden and for the European Randomised Study of Prostate Cancer.

Example reference: Karlsson et al (https://doi.org/10.1109/eScience.2016.7870915; https://doi.org/10.1371/journal.pone.0211918)

https://github.com/mclements/microsimulation

https://github.com/mclements/prostata

rstpm2 (R package)

R implementation of generalized survival models (GSMs), smooth accelerated failure time (AFT) models and Markov multi-state models.

Example reference: Liu et al (https://doi.org/10.1177/0962280216664760)

Links: https://cran.r-project.org/package=rstpm2

magree (R package)

Implements the O’Connell-Dobson-Schouten Estimators of Agreement for Multiple Observers

Example reference: Egevad et al (https://doi.org/10.1007/s00428-020-02858-w)

https://cran.r-project.org/package=magree

biostat3 (R package)

Utility functions, datasets and extended examples for survival analysis. This extends a range of other packages, some simple wrappers for time-to-event analyses, datasets, and extensive examples in HTML with R scripts. The package also supports the course Biostatistics III entitled “Survival analysis for epidemiologists in R”.

https://cran.r-project.org/package=biostat3