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Rostam M. Razban

dblp:228/0329 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2018
0000-0003-1055-4915ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular evolution
protein evolution
0.312018
ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes · Bioinform. 2018
Bioinformatics and computational biology
proteomics
0.112018
ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes · Bioinform. 2018

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

sequence evolutionary rate correlation · 0.3
YearPublicationVenuePosition
2018 ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes
abstract
Motivation: Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the Saccharomyces cerevisiae and Escherichia coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level. Results: We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S.cerevisiae and E.coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution. Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.49 (P-value < 10-10) and -0.46 (P-value < 10-10) for S.cerevisiae and E.coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant. Availability and implementation: ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
Rostam M. Razban, Amy Gilson, Niamh Durfee, Hendrik Strobelt, Kasper Dinkla, Jeong-Mo Choi, Hanspeter Pfister, Eugene I. Shakhnovich
Bioinform.1
2018 ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes
abstract
Bioinformatics (2018) https://doi.org/10.1093/bioinformatics/bty370 The publisher wishes to apologize for a mistake in Figure 1 in the above manuscript. The figure appears correctly below: The ProteomeVis web app after exploration has occurred. Hovering over asterisks located in the top-right corner of each panel opens an informational window. Pressing the help button (question mark symbol) located to the right of the Control Strip (A) leads to a quick tour. Alphabetical labels (A–E) are added to each component of ProteomeVis in this figure to introduce the tool in the text The paper has been corrected online.
Rostam M. Razban, Amy Gilson, Niamh Durfee, Hendrik Strobelt, Kasper Dinkla, Jeong-Mo Choi, Hanspeter Pfister, Eugene I. Shakhnovich
Bioinform.1