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Ignacio L. Ibarra

dblp:62/8323 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0002-0582-002XORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2 · 1 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
1 paper
Bioinformatics and computational biology · 67% Computing education · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education › STEM education
bioinformatics education
0.112010
Interactive software tool to comprehend the calculation of optimal sequence alignments with dynamic programming · Bioinform. 2010
Bioinformatics and computational biology › sequence alignment
dynamic programming alignment
0.112010
Interactive software tool to comprehend the calculation of optimal sequence alignments with dynamic programming · Bioinform. 2010
Bioinformatics and computational biology
sequence alignment
0.112010
Interactive software tool to comprehend the calculation of optimal sequence alignments with dynamic programming · Bioinform. 2010

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

graphical user interface · 0.1dynamic programming · 0.1
YearPublicationVenuePosition
2016 Efficient and automated large-scale detection of structural relationships in proteins with a flexible aligner
abstract
BACKGROUND: The total number of known three-dimensional protein structures is rapidly increasing. Consequently, the need for fast structural search against complete databases without a significant loss of accuracy is increasingly demanding. Recently, TopSearch, an ultra-fast method for finding rigid structural relationships between a query structure and the complete Protein Data Bank (PDB), at the multi-chain level, has been released. However, comparable accurate flexible structural aligners to perform efficient whole database searches of multi-domain proteins are not yet available. The availability of such a tool is critical for a sustainable boosting of biological discovery. RESULTS: Here we report on the development of a new method for the fast and flexible comparison of protein structure chains. The method relies on the calculation of 2D matrices containing a description of the three-dimensional arrangement of secondary structure elements (angles and distances). The comparison involves the matching of an ensemble of substructures through a nested-two-steps dynamic programming algorithm. The unique features of this new approach are the integration and trade-off balancing of the following: 1) speed, 2) accuracy and 3) global and semiglobal flexible structure alignment by integration of local substructure matching. The comparison, and matching with competitive accuracy, of one medium sized (250-aa) query structure against the complete PDB database (216,322 protein chains) takes about 8 min using an average desktop computer. The method is at least 2-3 orders of magnitude faster than other tested tools with similar accuracy. We validate the performance of the method for fold and superfamily assignment in a large benchmark set of protein structures. We finally provide a series of examples to illustrate the usefulness of this method and its application in biological discovery. CONCLUSIONS: The method is able to detect partial structure matching, rigid body shifts, conformational changes and tolerates substantial structural variation arising from insertions, deletions and sequence divergence, as well as structural convergence of unrelated proteins.
Fernando I. Gutiérrez, Felipe Rodriguez-Valenzuela, Ignacio L. Ibarra, Damien Devos, Francisco Melo 0001
BMC Bioinform.3
2010 Interactive software tool to comprehend the calculation of optimal sequence alignments with dynamic programming
abstract
SUMMARY: Dynamic programming (DP) is a general optimization strategy that is successfully used across various disciplines of science. In bioinformatics, it is widely applied in calculating the optimal alignment between pairs of protein or DNA sequences. These alignments form the basis of new, verifiable biological hypothesis. Despite its importance, there are no interactive tools available for training and education on understanding the DP algorithm. Here, we introduce an interactive computer application with a graphical interface, for the purpose of educating students about DP. The program displays the DP scoring matrix and the resulting optimal alignment(s), while allowing the user to modify key parameters such as the values in the similarity matrix, the sequence alignment algorithm version and the gap opening/extension penalties. We hope that this software will be useful to teachers and students of bioinformatics courses, as well as researchers who implement the DP algorithm for diverse applications. AVAILABILITY AND IMPLEMENTATION: The software is freely available at: http:/melolab.org/sat. The software is written in the Java computer language, thus it runs on all major platforms and operating systems including Windows, Mac OS X and LINUX. CONTACT: All inquiries or comments about this software should be directed to Francisco Melo at [email protected].
Ignacio L. Ibarra, Francisco Melo 0001
Bioinform.1