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Osvaldo Graña

dblp:26/3957 · also Osvaldo Graña-Castro · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0003-1615-4242ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › read mapping
pseudoalignment
0.712023
Pseudoalignment tools as an efficient alternative to detect repeated transposable elements in scRNAseq data · Bioinform. 2023
Bioinformatics and computational biology › single-cell analysis
single-cell RNA sequencing
0.712023
Pseudoalignment tools as an efficient alternative to detect repeated transposable elements in scRNAseq data · Bioinform. 2023
Bioinformatics and computational biology › epigenomics › DNA methylation › DNA methylation analysis
bisulfite sequencing
0.312018
Bicycle: a bioinformatics pipeline to analyze bisulfite sequencing data · Bioinform. 2018
Bioinformatics and computational biology › epigenomics › DNA methylation
DNA methylation analysis
0.312018
Bicycle: a bioinformatics pipeline to analyze bisulfite sequencing data · Bioinform. 2018
Bioinformatics and computational biology
epigenomics
0.312018
Bicycle: a bioinformatics pipeline to analyze bisulfite sequencing data · Bioinform. 2018
Bioinformatics and computational biology
sequence alignment
0.012004
SQUARE-determining reliable regions in sequence alignments · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

pseudoalignment · 0.7bisulfite sequencing pipeline · 0.3profile-based scoring · 0.0
YearPublicationVenuePosition
2023 Pseudoalignment tools as an efficient alternative to detect repeated transposable elements in scRNAseq data
abstract
MOTIVATION: Transposable elements (TE) have played a major role in configuring the structures of mammalian genomes through evolution. In normal conditions, the expression of these elements is repressed by different epigenetic regulation mechanisms such as DNA methylation, histone modification and regulation by small RNAs. TE re-activation is associated with stemness potential acquisition, regulation of innate immunity and disease, such as cancer. However, the vast majority of current knowledge in the field is based on bulk expression studies, and very little is known on cell-type- or state-specific expression of TE-derived transcripts. Therefore, cost-efficient single-cell-resolution TE expression analytical approaches are needed. RESULTS: We have implemented an analytical approach based on pseudoalignment to consensus sequences to incorporate TE expression information to scRNAseq data. AVAILABILITY AND IMPLEMENTATION: All the data and code implemented are available as Supplementary data and in: https://github.com/jmzvillarreal/kallisto_TE_scRNAseq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Jaime Martínez de Villarreal, Mark Kalisz, Gabriel Piedrafita, Osvaldo Graña, Dafni Chondronasiou, Manuel Serrano, Francisco X. Real
Bioinform.4
2018 Bicycle: a bioinformatics pipeline to analyze bisulfite sequencing data
abstract
Summary: High-throughput sequencing of bisulfite-converted DNA is a technique used to measure DNA methylation levels. Although a considerable number of computational pipelines have been developed to analyze such data, none of them tackles all the peculiarities of the analysis together, revealing limitations that can force the user to manually perform additional steps needed for a complete processing of the data. This article presents bicycle, an integrated, flexible analysis pipeline for bisulfite sequencing data. Bicycle analyzes whole genome bisulfite sequencing data, targeted bisulfite sequencing data and hydroxymethylation data. To show how bicycle overtakes other available pipelines, we compared them on a defined number of features that are summarized in a table. We also tested bicycle with both simulated and real datasets, to show its level of performance, and compared it to different state-of-the-art methylation analysis pipelines. Availability and implementation: Bicycle is publicly available under GNU LGPL v3.0 license at http://www.sing-group.org/bicycle. Users can also download a customized Ubuntu LiveCD including bicycle and other bisulfite sequencing data pipelines compared here. In addition, a docker image with bicycle and its dependencies, which allows a straightforward use of bicycle in any platform (e.g. Linux, OS X or Windows), is also available. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Osvaldo Graña, Hugo López-Fernández, Florentino Fernández Riverola, David G. Pisano, Daniel Glez-Peña
Bioinform.1
2004 SQUARE-determining reliable regions in sequence alignments
abstract
The Server for Quick Alignment Reliability Evaluation (SQUARE) is a Web-based version of the method we developed to predict regions of reliably aligned residues in sequence alignments. Given an alignment between a query sequence and a sequence of known structure, SQUARE is able to predict which residues are reliably aligned. The server accesses a database of profiles of sequences of known three-dimensional structures in order to calculate the scores for each residue in the alignment. SQUARE produces a graphical output of the residue profile-derived alignment scores along with an indication of the reliability of the alignment. In addition, the scores can be compared against template secondary structure, conserved residues and important sites.
Michael L. Tress, Osvaldo Graña, Alfonso Valencia
Bioinform.2