Demo Data from VLDB 2026 / reviewers in the wild / expert
Rodrigo Gouveia-Oliveira
dblp:21/6930
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2009
0009-0007-5921-6438ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 2 first-author
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
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › molecular evolution
protein coevolution |
0.1 | 1 | 2009 | InterMap3D: predicting and visualizing co-evolving protein residues · Bioinform. 2009 |
Bioinformatics and computational biology › sequence analysis
sequence comparison |
0.0 | 1 | 2004 | Comparative evaluation of word composition distances for the recognition of SCOP relationships · Bioinform. 2004 |
Bioinformatics and computational biology › structural bioinformatics › protein structure representation
protein structure visualization |
0.0 | 1 | 2009 | InterMap3D: predicting and visualizing co-evolving protein residues · Bioinform. 2009 |
Bioinformatics and computational biology › structural bioinformatics
protein structure classification |
0.0 | 1 | 2004 | Comparative evaluation of word composition distances for the recognition of SCOP relationships · Bioinform. 2004 |
Methods — techniques the papers use, named apart from their topics
row and column weighting · 0.1mutual information · 0.1dependency · 0.1word composition metrics · 0.0smith-waterman · 0.0ROC analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | InterMap3D: predicting and visualizing co-evolving protein residuesabstractSUMMARY: InterMap3D predicts co-evolving protein residues and plots them on the 3D protein structure. Starting with a single protein sequence, InterMap3D automatically finds a set of homologous sequences, generates an alignment and fetches the most similar 3D structure from the Protein Data Bank (PDB). It can also accept a user-generated alignment. Based on the alignment, co-evolving residues are then predicted using three different methods: Row and Column Weighing of Mutual Information, Mutual Information/Entropy and Dependency. Finally, InterMap3D generates high-quality images of the protein with the predicted co-evolving residues highlighted. AVAILABILITY: http://www.cbs.dtu.dk/services/InterMap3D/. Rodrigo Gouveia-Oliveira, Francisco S. Roque, Rasmus Wernersson, Thomas Sicheritz-Pontén, Peter Wad Sackett, Anne Mølgaard, Anders Gorm Pedersen |
Bioinform. | 1 |
| 2007 | MaxAlign: maximizing usable data in an alignmentabstractBACKGROUND: The presence of gaps in an alignment of nucleotide or protein sequences is often an inconvenience for bioinformatical studies. In phylogenetic and other analyses, for instance, gapped columns are often discarded entirely from the alignment. RESULTS: MaxAlign is a program that optimizes the alignment prior to such analyses. Specifically, it maximizes the number of nucleotide (or amino acid) symbols that are present in gap-free columns - the alignment area - by selecting the optimal subset of sequences to exclude from the alignment. MaxAlign can be used prior to phylogenetic and bioinformatical analyses as well as in other situations where this form of alignment improvement is useful. In this work we test MaxAlign's performance in these tasks and compare the accuracy of phylogenetic estimates including and excluding gapped columns from the analysis, with and without processing with MaxAlign. In this paper we also introduce a new simple measure of tree similarity, Normalized Symmetric Similarity (NSS) that we consider useful for comparing tree topologies. CONCLUSION: We demonstrate how MaxAlign is helpful in detecting misaligned or defective sequences without requiring manual inspection. We also show that it is not advisable to exclude gapped columns from phylogenetic analyses unless MaxAlign is used first. Finally, we find that the sequences removed by MaxAlign from an alignment tend to be those that would otherwise be associated with low phylogenetic accuracy, and that the presence of gaps in any given sequence does not seem to disturb the phylogenetic estimates of other sequences. The MaxAlign web-server is freely available online at http://www.cbs.dtu.dk/services/MaxAlign where supplementary information can also be found. The program is also freely available as a Perl stand-alone package. Rodrigo Gouveia-Oliveira, Peter Wad Sackett, Anders Gorm Pedersen |
BMC Bioinform. | 1 |
| 2004 | Comparative evaluation of word composition distances for the recognition of SCOP relationshipsabstractMOTIVATION: Alignment-free metrics were recently reviewed by the authors, but have not until now been object of a comparative study. This paper compares the classification accuracy of word composition metrics therein reviewed. It also presents a new distance definition between protein sequences, the W-metric, which bridges between alignment metrics, such as scores produced by the Smith-Waterman algorithm, and methods based solely in L-tuple composition, such as Euclidean distance and Information content. RESULTS: The comparative study reported here used the SCOP/ASTRAL protein structure hierarchical database and accessed the discriminant value of alternative sequence dissimilarity measures by calculating areas under the Receiver Operating Characteristic curves. Although alignment methods resulted in very good classification accuracy at family and superfamily levels, alignment-free distances, in particular Standard Euclidean Distance, are as good as alignment algorithms when sequence similarity is smaller, such as for recognition of fold or class relationships. This observation justifies its advantageous use to pre-filter homologous proteins since word statistics techniques are computed much faster than the alignment methods. AVAILABILITY: All MATLAB code used to generate the data is available upon request to the authors. Additional material available at http://bioinformatics.musc.edu/wmetric Susana Vinga, Rodrigo Gouveia-Oliveira, Jonas S. Almeida |
Bioinform. | 2 |