Welcome to the Computational Genomics Institute Projects, here you can find all the information related to the different projects at which we are working at, this information comprise:
  • Tutorials for end users
  • Technical information for developers
  • Roadmap for the new features we are working in
  • Some known issues and planned enhancements
  • Many documents and files of publications and releases
  • Some courses that are going to be held

Genes operate within an intricate network of interactions that we have only recently started to envisage. Many higher-order levels of interaction are continuously being discovered.
We are interested in developing methods and tools which can help to understand large-scale experiments from a systems biology perspective. From the last years w

Some of our projects are:
  • Labs: the projects that are being developed at this moment.

You can also browse all our projects in here

Latest news

Babelomics: Babelomics 4 at the top 5% of NAR papers
We are pleased to inform that Babelomics 4 has been chosen by the Editors of Nucleic Acids Research to appear on their Featured Articles page
Added by Ignacio Medina about 9 years ago

Babelomics: Babelomics 4.0.1 released
A maintenance bug fix release of Babelomics 4
Added by Ignacio Medina about 9 years ago

Babelomics: VI International Course of Massive Data Analysis
6th Edition of the MDA course in CIPF (Valencia)
Added by Ignacio Medina about 9 years ago

Babelomics: Babelomics 4.0 release!
GEPAS suite has been merged in this new release of Babelomics with many new features and improvements
Added by Ignacio Medina about 10 years ago

View all news

Latest projects

  • HPG Aligner (11/05/2012 02:01 pm)

    As sequencing technologies progress the amount of data produced grows exponentially, shifting the bottleneck of discovery towards the data analysis phase. Here we present an innovative approach that combines reengineering, optimization and parallelization of the algorithms which results in a significant increase of the mapping sensitivity over a wide range of read lengths and substantial shorter runtimes when compared to other NGS mapping solutions currently available. Moreover, our software has been implemented using High-Performance computing (HPC) technologies such as OpenMP for multi-core CPUs, SSE and Nvidia CUDA for GPUs, besides, comparatively, the performance of this approach scales up very efficiently with the number of processors, therefore our implementation is ready to take advantage of new CPUs and GPUs....

  • HPG-SW (07/30/2012 10:34 am)

    HPG-SW is a modern implementation of the Smith-Waterman algorithm based on high-performance computing techniques. HPG-SW uses the OpenMP parallel programming model and the SSE instructions in order to take advantages of the multi-core processors and the SIMD registers of current CPU cores....

  • HPG-VCF tools (06/04/2012 04:55 pm)

    Biologists receive so much biological data that they have to spend a lot of time cleaning it up in order to get just the data they are interested in. HPG VCF Tools is a set of tools for preprocessing, filtering and manipulating VCF files. It aims to avoid excessive time consumption in tedious preprocessing tasks....

  • HPG-fastq tools (06/04/2012 03:19 pm)

    New high-throughput sequencers are able to produce data at an unprecedented scale while sequencing costs are in free fall. Primary sequence data management involves an unavoidable step of quality control and pre-processing and is computationally expensive. There are some solutions available to carry out a quality control check, however they are slow and the report is based only in the partial analysis of the data. We present a High Performance Computing (HPC) solution for quality control check of the widely used standard FASTQ that identifies and exploits the hardware (CPUs and GPUs) available in the computer in which it is running. This solution outperforms 5x any conventional solution based on CPU processors. Moreover, the QC is exhaustive and it also carries out several preprocessing steps on the data....

  • High Performance Genomics (HPG) (06/04/2012 03:11 pm)

    HPG stands for High Performance Genomics. The goal of this of project is to provide a complete suite of advanced computing solutions to solve the current computational problems in the field of genomics, especially in the field of massive sequencing or NGS. This computing solutions range from High Performance Computing (HPC) or Cloud-based solutions for the processing, analysis o visualization of genome-scale data....