BOL

github.com - It is designed to work with patterned data. Famous examples of problems related to patterned data are: recovering signals in networks after a stimulation (cascade network reverse engineering), analysing periodic signals.

ivory.idyll.org - DNA k-mers underlie much of our assembly work, and we (along with many others!) have spent a lot of time thinking about how to store k-mer graphs efficiently, discard redundant data, and count them efficiently. More recently, we've...

homes.sice.indiana.edu - Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models...

www.nature.com - Because of the increasing size and inherent complexity of biological data, there has been an increase in the application of machine learning in biology to create useful and predictive models of the underlying biological processes. All machine...

www.nature.com - We aim to provide readers with a gentle introduction to a few key machine learning techniques, including the most recently developed and widely used techniques involving deep neural networks. We describe how different techniques may be suited to...

The Brent Lab is developing and applying computational methods for mapping gene regulation networks, modeling them quantitatively, and engineering new behaviors into them.

SPAdes—St. Petersburg genome Assembler—was originally developed for de novo assembly of genome sequencing data produced for cultivated microbial isolates and for single-cell genomic DNA sequencing. With time, the functionality of SPAdes...

The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions.

www.bioconductor.org - statistical analysis and visulization of functional profiles for genes and gene clustersBioconductor version: Release (3.3)This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.Author:...

web.mit.edu - The following is a step-by-step guide to creating your own R package.  Even beyond this course, youmay find this useful for storing functions you create for your own research or for editing existingR packages to suit your needs. This guide...