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Rohit Ghai

dblp:29/3110 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2007
0000-0002-0591-6152ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 4 · 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 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
comparative genomics
0.122007
GECO-linear visualization for comparative genomics · Bioinform. 2007
Augur - a computational pipeline for whole genome microbial surface protein prediction and classification · Bioinform. 2006
Bioinformatics and computational biology › genomics
genome visualization
0.112007
GECO-linear visualization for comparative genomics · Bioinform. 2007
Bioinformatics and computational biology › genomics › microbial genomics
bacterial genomics
0.112006
Augur - a computational pipeline for whole genome microbial surface protein prediction and classification · Bioinform. 2006
Bioinformatics and computational biology › computational microbiology
microbial genome analysis
0.112006
Augur - a computational pipeline for whole genome microbial surface protein prediction and classification · Bioinform. 2006
Bioinformatics and computational biology › protein function prediction
protein classification
0.112006
Augur - a computational pipeline for whole genome microbial surface protein prediction and classification · Bioinform. 2006
Bioinformatics and computational biology
protein function prediction
0.112006
Augur - a computational pipeline for whole genome microbial surface protein prediction and classification · Bioinform. 2006
Bioinformatics and computational biology › comparative genomics › orthology analysis
ortholog identification
0.012007
GECO-linear visualization for comparative genomics · Bioinform. 2007

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

BLASTCLUST · 0.1visualization · 0.1surface prediction algorithms · 0.1
YearPublicationVenuePosition
2007 GECO-linear visualization for comparative genomics
abstract
UNLABELLED: In order to understand and interpret phylogenetic and functional relationships between multiple prokaryotic species, qualitative and quantitative data must be correlated and displayed. GECO allows linear visualization of multiple genomes using a client/server based approach by dynamically creating .png- or .pdf-formatted images. It is able to display ortholog relations calculated using BLASTCLUST by color coding ortholog representations. Irregularities on the genomic level can be identified by anomalous G/C composition. Thus, this software will enable researchers to detect horizontally transferred genes, pseudogenes and insertions/deletions in related microbial genomes. AVAILABILITY: http://bioinfo.mikrobio.med.uni-giessen.de/geco2/GecoMainServlet
C. T. Kuenne, Rohit Ghai, Trinad Chakraborty, Torsten Hain
Bioinform.2
2006 Augur - a computational pipeline for whole genome microbial surface protein prediction and classification
abstract
UNLABELLED: The analysis of protein function is a challenge and a major bottleneck towards well-annotated and analysed microbial genomes. In particular, bacterial surface proteins present an opportunity for pharmacological intervention and vaccine development. We present Augur, an automatic prediction pipeline that integrates major surface prediction algorithms and enables comparative analysis, classification and visualization for gram-positive bacteria on a genomic scale. AVAILABILITY: http://bioinfo.mikrobio.med.uni-giessen.de/augur
André Billion, Rohit Ghai, Trinad Chakraborty, Torsten Hain
Bioinform.2
2006 Integrated functional visualization of eukaryotic genomes
abstract
BACKGROUND: Increasing amounts of data from large scale whole genome analysis efforts demands convenient tools for manipulation, visualization and investigation. Whole genome plots offer an intuitive window to the analysis. We describe two applications that enable users to easily plot and explore whole genome data from their own or other researchers' experiments. RESULTS: STRIPE and GFFtool (General Feature Format Tool) are softwares designed to support integration, visualization and exploration of whole genome data from eukaryotic genomes. STRIPE, in addition to providing a highly customizable and interactive data plot, provides access to numerous well-selected databases with updated information on all genes of a genome. GFFtool provides a user-friendly solution to integrating experimental data with the genomic information available in public databases. They also obviate the need for users to maintain large annotation resources, as they link to well-known resources using standard gene and protein identifiers. CONCLUSION: The programs provide the user with broad genomic overviews of data distribution, fast access to data of interest, and the ability to navigate speedily from one resource to another, and gain a better understanding of result of whole genome analysis experiments.
Rohit Ghai, Hannes Lindemann, Trinad Chakraborty
BMC Bioinform.1
2004 GenomeViz: visualizing microbial genomes
abstract
BACKGROUND: An increasing number of microbial genomes are being sequenced and deposited in public databases. In addition, several closely related strains are also being sequenced in order to understand the genetic basis of diversity and mechanisms that lead to the acquisition of new genetic traits. These exercises have necessitated the requirement for visualizing microbial genomes and performing genome comparisons on a finer scale. We have developed GenomeViz to enable rapid visualization and subsequent comparisons of several microbial genomes in an interactive environment. RESULTS: Here we describe a program that allows visualization of both qualitative and quantitative information from complete and partially sequenced microbial genomes. Using GenomeViz, data deriving from studies on genomic islands, gene/protein classifications, GC content, GC skew, whole genome alignments, microarrays and proteomics may be plotted. Several genomes can be visualized interactively at the same time from a comparative genomic perspective and publication quality circular genome plots can be created. CONCLUSIONS: GenomeViz should allow researchers to perform visualization and comparative analysis of up to eight different microbial genomes simultaneously.
Rohit Ghai, Torsten Hain, Trinad Chakraborty
BMC Bioinform.1