EDBT 2026 Demo / reviewers in the wild / expert
Naresh Raviswaran
dblp:93/3364
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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 › biocuration
literature curation |
0.1 | 1 | 2008 | MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactions · Bioinform. 2008 |
Bioinformatics and computational biology › biological database
protein interaction database |
0.1 | 1 | 2008 | MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactions · Bioinform. 2008 |
Bioinformatics and computational biology
protein-protein interaction prediction |
0.1 | 1 | 2008 | MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactions · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
text mining · 0.1genomic context · 0.1co-expression analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactionsabstractUNLABELLED: Prokaryotic protein-protein interactions are underrepresented in currently available databases. Here, we describe a 'gold standard' dataset (MPI-LIT) focusing on microbial binary protein-protein interactions and associated experimental evidence that we have manually curated from 813 abstracts and full texts that were selected from an initial set of 36 852 abstracts. The MPI-LIT dataset comprises 1237 experimental descriptions that describe a non-redundant set of 746 interactions of which 659 (88%) are not reported in public databases. To estimate the curation quality, we compared our dataset with a union of microbial interaction data from IntAct, DIP, BIND and MINT. Among common abstracts, we achieve a sensitivity of up to 66% for interactions and 75% for experimental methods. Compared with these other datasets, MPI-LIT has the lowest fraction of interaction experiments per abstract (0.9) and the highest coverage of strains (92) and scientific articles (813). We compared methods that evaluate functional interactions among proteins (such as genomic context or co-expression) which are implemented in the STRING database. Most of these methods discriminate well between functionally relevant protein interactions (MPI-LIT) and high-throughput data. AVAILABILITY: http://www.jcvi.org/mpidb/interaction.php?dbsource=MPI-LIT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Seesandra V. Rajagopala, Johannes Goll, N. D. Deve Gowda, Kumar C. Sunil, Bjoern Titz, Sharmila S. Mary, Naresh Raviswaran, Chetan S. Poojari, Srinivas Ramachandra, Svetlana Shtivelband, Stephen M. Blazie, Julia Hofmann, Peter Uetz |
Bioinform. | 8 |