Syed Asad Rahman

dblp:38/1167 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2016
0000-0002-7602-6675ORCID · verified

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

Applied, interdisciplinary, general and emerging computing · 4 · 4 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
3 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
metabolic pathway analysis
0.322016
Reaction Decoder Tool (RDT): extracting features from chemical reactions · Bioinform. 2016
Metabolic pathway analysis web service (Pathway Hunter Tool at CUBIC) · Bioinform. 2005
Bioinformatics and computational biology › molecular informatics › cheminformatics
atom mapping
0.212016
Reaction Decoder Tool (RDT): extracting features from chemical reactions · Bioinform. 2016
Bioinformatics and computational biology
enzymatic reaction analysis
0.212016
Reaction Decoder Tool (RDT): extracting features from chemical reactions · Bioinform. 2016
Bioinformatics and computational biology › systems biology
metabolic network analysis
0.122006
Observing local and global properties of metabolic pathways: "load points" and "choke points" in the metabolic networks · Bioinform. 2006
Metabolic pathway analysis web service (Pathway Hunter Tool at CUBIC) · Bioinform. 2005
Bioinformatics and computational biology › drug discovery › target identification
drug target identification
0.012006
Observing local and global properties of metabolic pathways: "load points" and "choke points" in the metabolic networks · Bioinform. 2006

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

dynamic programming · 0.2graph theory · 0.1k-shortest paths · 0.1chemical structure similarity · 0.1
YearPublicationVenuePosition
2016 Reaction Decoder Tool (RDT): extracting features from chemical reactions
abstract
UNLABELLED: Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. AVAILABILITY AND IMPLEMENTATION: This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder CONTACT: : [email protected] or [email protected].
Syed Asad Rahman, Gilliean Torrance, Lorenzo Baldacci, Sergio Martínez Cuesta, Franz Fenninger, Nimish Gopal, Saket Choudhary, John W. May, Gemma L. Holliday, Christoph Steinbeck, Janet M. Thornton
Bioinform.1
2006 Observing local and global properties of metabolic pathways: "load points" and "choke points" in the metabolic networks
abstract
MOTIVATION: The local and global aspects of metabolic network analyses allow us to identify enzymes or reactions that are crucial for the survival of the organism(s), therefore directing us towards the discovery of potential drug targets. RESULTS: We demonstrate a new method ('load points') to rank the enzymes/metabolites in the metabolic network and propose a model to determine and rank the biochemical lethality in metabolic networks (enzymes/metabolites) through 'choke points'. Based on an extended form of the graph theory model of metabolic networks, metabolite structural information was used to calculate the k-shortest paths between metabolites (the presence of more than one competing path between substrate and product). On the basis of these paths and connectivity information, load points were calculated and used to empirically rank the importance of metabolites/enzymes in the metabolic network. The load point analysis emphasizes the role that the biochemical structure of a metabolite, rather than its connectivity (hubs), plays in the conversion pathway. In order to identify potential drug targets (based on the biochemical lethality of metabolic networks), the concept of choke points and load points was used to find enzymes (edges) which uniquely consume or produce a particular metabolite (nodes). A non-pathogenic bacterial strain Bacillus subtilis 168 (lactic acid producing bacteria) and a related pathogenic bacterial strain Bacillus anthracis Sterne (avirulent but toxigenic strain, producing the toxin Anthrax) were selected as model organisms. The choke point strategy was implemented on the pathogen bacterial network of B.anthracis Sterne. Potential drug targets are proposed based on the analysis of the top 10 choke points in the bacterial network. A comparative study between the reported top 10 bacterial choke points and the human metabolic network was performed. Further biological inferences were made on results obtained by performing a homology search against the human genome. AVAILABILITY: The load and choke point modules are introduced in the Pathway Hunter Tool (PHT), the basic version of which is available on http://www.pht.uni-koeln.de.
Syed Asad Rahman, Dietmar Schomburg
Bioinform.1
2005 Metabolic pathway analysis web service (Pathway Hunter Tool at CUBIC)
abstract
MOTIVATION: Pathway Hunter Tool (PHT), is a fast, robust and user-friendly tool to analyse the shortest paths in metabolic pathways. The user can perform shortest path analysis for one or more organisms or can build virtual organisms (networks) using enzymes. Using PHT, the user can also calculate the average shortest path (Jungnickel, 2002 Graphs, Network and Algorithm. Springer-Verlag, Berlin), average alternate path and the top 10 hubs in the metabolic network. The comparative study of metabolic connectivity and observing the cross talk between metabolic pathways among various sequenced genomes is possible. RESULTS: A new algorithm for finding the biochemically valid connectivity between metabolites in a metabolic network was developed and implemented. A predefined manual assignment of side metabolites (like ATP, ADP, water, CO(2) etc.) and main metabolites is not necessary as the new concept uses chemical structure information (global and local similarity) between metabolites for identification of the shortest path.
Syed Asad Rahman, P. Advani, R. Schunk, Rainer Schrader, Dietmar Schomburg
Bioinform.1
2005 Metabolic Network Analysis: Implication And Application
abstract
metabolic pathway alignmentload pointchoke pointdrug targetpathway analysisconserved pathwaysalternate pathsshortest path
Syed Asad Rahman, Pardha Saradhi Jonnalagadda, Jyothi Padiadpu, Kai Hartmann, Rainer Schrader, Dietmar Schomburg
BMC Bioinform.1