Demo Data from EDBT 2026 / reviewers in the wild / expert
Paul A. Thiessen
dblp:50/4118
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3
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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence alignment
protein sequence alignment |
0.1 | 1 | 2005 | A structure-based method for protein sequence alignment · Bioinform. 2005 |
Bioinformatics and computational biology
protein sequence analysis |
0.1 | 1 | 2005 | A structure-based method for protein sequence alignment · Bioinform. 2005 |
Bioinformatics and computational biology › structural bioinformatics
structure-based sequence alignment |
0.1 | 1 | 2005 | A structure-based method for protein sequence alignment · Bioinform. 2005 |
Methods — techniques the papers use, named apart from their topics
profile alignment · 0.1position-specific scoring matrix · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | State of the art: refinement of multiple sequence alignmentsabstractCorrection to Chakrabarti S, Lanczycki CJ, Panchenko AR, Przytycka TM, Thiessen PA and Bryant SH: State of the art: refinement of multiple sequence alignments. BMC Bioinformatics 2006, 7:499. Saikat Chakrabarti 0001, Christopher J. Lanczycki, Anna R. Panchenko, Teresa M. Przytycka, Paul A. Thiessen, Stephen H. Bryant |
BMC Bioinform. | 5 |
| 2006 | State of the art: refinement of multiple sequence alignmentsabstractBACKGROUND: Accurate multiple sequence alignments of proteins are very important in computational biology today. Despite the numerous efforts made in this field, all alignment strategies have certain shortcomings resulting in alignments that are not always correct. Refinement of existing alignment can prove to be an intelligent choice considering the increasing importance of high quality alignments in large scale high-throughput analysis. RESULTS: We provide an extensive comparison of the performance of the alignment refinement algorithms. The accuracy and efficiency of the refinement programs are compared using the 3D structure-based alignments in the BAliBASE benchmark database as well as manually curated high quality alignments from Conserved Domain Database (CDD). CONCLUSION: Comparison of performance for refined alignments revealed that despite the absence of dramatic improvements, our refinement method, REFINER, which uses conserved regions as constraints performs better in improving the alignments generated by different alignment algorithms. In most cases REFINER produces a higher-scoring, modestly improved alignment that does not deteriorate the well-conserved regions of the original alignment. Saikat Chakrabarti 0001, Christopher J. Lanczycki, Anna R. Panchenko, Teresa M. Przytycka, Paul A. Thiessen, Stephen H. Bryant |
BMC Bioinform. | 5 |
| 2005 | A structure-based method for protein sequence alignmentabstractMOTIVATION: With the continuing rapid growth of protein sequence data, protein sequence comparison methods have become the most widely used tools of bioinformatics. Among these methods are those that use position-specific scoring matrices (PSSMs) to describe protein families. PSSMs can capture information about conserved patterns within families, which can be used to increase the sensitivity of searches for related sequences. Certain types of structural information, however, are not generally captured by PSSM search methods. Here we introduce a program, Structure-based ALignment TOol (SALTO), that aligns protein query sequences to PSSMs using rules for placing and scoring gaps that are consistent with the conserved regions of domain alignments from NCBI's Conserved Domain Database. RESULTS: In most cases, the alignment scores obtained using the local alignment version follow an extreme value distribution. SALTO's performance in finding related sequences and producing accurate alignments is similar to or better than that of IMPALA; one advantage of SALTO is that it imposes an explicit gapping model on each protein family. AVAILABILITY: A stand-alone version of the program that can generate global or local alignments is available by ftp distribution (ftp://ftp.ncbi.nih.gov/pub/SALTO/), and has been incorporated to Cn3D structure/alignment viewer. CONTACT: [email protected]. Maricel G. Kann, Paul A. Thiessen, Anna R. Panchenko, Alejandro A. Schäffer, Stephen F. Altschul, Stephen H. Bryant |
Bioinform. | 2 |