Search Results for "es1-2016-leic1pl-81"

ExRandom is a small header-only C++11 library for exact sampling from the normal, exponential, and discrete normal distributions (provided that the underlying generator is perfect). This library provides an implementation of the algorithms described in C. F. F. Karney, Sampling exactly from the normal distribution, ACM Trans. Math. Software 42(1), 3:1-14 (Jan. 2016), https://doi.org/10.1145/2710016, https://arxiv.org/abs/1303.6257.

Gaol: NOT Just Another Interval Library Gaol is a C++ library for interval arithmetic. It is supposed to be a fast and easy to use/modify library for anyone interested in assessing interval arithmetic merits or using it on a regular basis. WARNING: starting October 2016, the new location for GAOL is http://frederic.goualard.net/#research-software. Sourceforge and the Sourceforge Subversion repository will no longer be used.

BioFVM is an open source diffusive transport solver for biological problems. It can solve for the diffusion of tens or hundreds of substrates on large 3-D domains. For simplicity, the code has minimal external dependencies. BioFVM was first published in: A. Ghaffarizadeh, S.H. Friedman, and P. Macklin. BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations. Bioinformatics 32(8): 1156-8, 2016. DOI: 10.1093/bioinformatics/btv730 method paper...

The Free Finite Element Package is a library which contains numerical methods required when working with finite elements. The goal of FFEP is to provide basic functions for approximating the solution of elliptic and parabolic PDEs in 2D. Until 2016 FFEP was developed using C. Science 2016 the language was switched to GNU Octave with some C Mex-Functions. Mesh generation or import is not part of FFEP. We recommend the use of Gmsh.

..., Programming student in Portugal Support or Contact Having trouble with software? Contact pedro.luzio.cloud@gmail.com and we’ll help you sort it out. 2016-06-13

Riboshape is a suite of algorithms to predict ribosome footprint profile shapes from transcript sequences. It applies kernel smoothing to codon sequences to build predictive features, and uses these features to builds a sparse regression model to predict the ribosome footprint profile shapes. Reference: Liu, T.-Y. and Song, Y.S. Prediction of ribosome footprint profile shapes from transcript sequences. Proceedings of ISMB 2016, Bioinformatics, Vol. 32 No. 12 (2016) i183-i191.