OptFlux

OptFlux is an open-source and modular software to support in silico metabolic engineering tasks aimed at being the reference computational application in the field.

A major new release of OptFlux is now available, with several important improvements and new features.

CoBAMP

CoBAMP (Constraint-Based Analysis of Metabolic Pathways) is a Python package containing pathway analysis methods for use with constraint-based metabolic models. The main purpose is to provide a framework that is both modular and flexible enough to be integrated in other packages (such as cobrapy, framed or cameo) that already implement generic data structures for metabolic models.

merlin

merlin is a simple, graphical and user-oriented solution for the reconstruction of genome-scale metabolic models. It will guide you along the model reconstruction, providing several tools that help to improve and curate the model throughout the whole process.

WebSpecmine

WebSpecmine is a web-based application designed to perform the analysis of metabolomics data based on spectroscopic and chromatographic techniques (NMR, Infrared, UV-visible, and Raman, and LC/GC-MS)) and compound concentrations.

Summer School in Metabolic Modelling @ University of Minho

We are pleased to announce the Summer School in Metabolic Modelling that will be held at University of Minho in Braga, Portugal from 3-7 of June 2019. This 5-day duration summer school will focus on user-friendly tools for metabolic model reconstruction and simulation and experimental procedures to improve those models. The course is directed to everyone who is interested in learning to use metabolic modelling in their research, using user-friendly tools. No programming skills are required.

Single-cell RNA-Seq analysis using a Seurat based graphical interface

This workshop, to be hosted in the afternoon of Bioinformatics Open Days 2020, is an introduction to differential gene expression analysis of medium-sized single-cell RNA-seq (scRNA-seq) obtained using the 10x Genomics Chromium System. Participants will learn about the basic concepts behind the technology, its applications and concepts, and go through a hands-on exercise where they will perform a re-analysis of a sample of ~3,000 cells from the Mouse Cell Atlas (MCA).