@article {9,
	title = {Genome Maps, a new generation genome browser.},
	journal = {Nucleic Acids Res},
	volume = {41},
	year = {2013},
	month = {2013 Jul},
	pages = {W41-6},
	abstract = {<p>Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.</p>},
	keywords = {Genome, Genomics, Internet, Software},
	issn = {1362-4962},
	doi = {10.1093/nar/gkt530},
	author = {Medina, Ignacio and Salavert, Francisco and Sanchez, Rub{\'e}n and de Maria, Alejandro and Alonso, Roberto and Escobar, Pablo and Bleda, Marta and Dopazo, Joaqu{\'\i}n}
}
@article {4,
	title = {Using GPUs for the Exact Alignment of Short-Read Genetic Sequences by Means of the Burrows-Wheeler Transform},
	journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)},
	volume = {9},
	year = {2012},
	month = {2012},
	chapter = {1245},
	abstract = {General Purpose Graphic Processing Units (GPGPUs) constitute an inexpensive resource for computing-intensive applications that could exploit an intrinsic fine-grain parallelism. This paper presents the design and implementation in GPGPUs of an exact alignment tool for nucleotide sequences based on the Burrows-Wheeler Transform. We compare this algorithm with state-of-the-art implementations of the same algorithm over standard CPUs, and considering the same conditions in terms of I/O. Excluding disk transfers, the implementation of the algorithm in GPUs shows a speedup larger than 12{\times}, when compared to CPU execution. This implementation exploits the parallelism by concurrently searching different sequences on the same reference search tree, maximizing memory locality and ensuring a symmetric access to the data. The paper describes the behavior of the algorithm in GPU, showing a good scalability in the performance, only limited by the size of the GPU inner memory.},
	issn = {1545-5963},
	doi = {10.1109/TCBB.2012.49},
	url = {http://dl.acm.org/citation.cfm?id=2223945},
	author = {Jose Salavert Torres and Ignacio Blanquer Espert and Andres Tomas Dominguez and Vicente Hernendez and Medina, Ignacio and Joaquin Terraga and Dopazo, Joaqu{\'\i}n}
}
