EDBT 2026 Demo / reviewers in the wild / expert
Markus Krummenacker
dblp:53/3311
· DBLP profile ↗
10ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-2546-3007ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 10 · 1 first-author · 1 since 2021
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
5 papers |
Bioinformatics and computational biology · 100% |
Topics — the 9 heaviest of 12, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology
metabolic network analysis |
0.3 | 2 | 2014 | Optimal metabolic route search based on atom mappings · Bioinform. 2014 Construction and completion of flux balance models from pathway databases · Bioinform. 2012 |
Bioinformatics and computational biology › systems biology
metabolic modeling |
0.2 | 1 | 2016 | Representation and inference of cellular architecture for metabolic reconstruction and modeling · Bioinform. 2016 |
Bioinformatics and computational biology › molecular informatics › cheminformatics
atom mapping |
0.2 | 1 | 2014 | Optimal metabolic route search based on atom mappings · Bioinform. 2014 |
Bioinformatics and computational biology › systems bioinformatics
metabolic route search |
0.2 | 1 | 2014 | Optimal metabolic route search based on atom mappings · Bioinform. 2014 |
Bioinformatics and computational biology › systems biology › constraint-based modeling
flux balance analysis |
0.1 | 1 | 2012 | Construction and completion of flux balance models from pathway databases · Bioinform. 2012 |
Bioinformatics and computational biology › ontology
ontology development |
0.1 | 1 | 2016 | Representation and inference of cellular architecture for metabolic reconstruction and modeling · Bioinform. 2016 |
Bioinformatics and computational biology
biological database |
0.1 | 1 | 2005 | Querying and computing with BioCyc databases · Bioinform. 2005 |
Bioinformatics and computational biology › biological database
pathway database |
0.1 | 1 | 2005 | Querying and computing with BioCyc databases · Bioinform. 2005 |
Bioinformatics and computational biology › sequence analysis
sequence classification |
0.0 | 1 | 1997 | Prediction of Enzyme Classification from Protein Sequence without the Use of Sequence Similarity · ISMB 1997 |
Methods — techniques the papers use, named apart from their topics
ontology inference · 0.2branch-and-bound search · 0.2mixed integer linear programming · 0.1SQL · 0.1API access · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Pathway Tools version 23.0 update: software for pathway/genome informatics and systems biologyabstractAbstract Motivation Biological systems function through dynamic interactions among genes and their products, regulatory circuits and metabolic networks. Our development of the Pathway Tools software was motivated by the need to construct biological knowledge resources that combine these many types of data, and that enable users to find and comprehend data of interest as quickly as possible through query and visualization tools. Further, we sought to support the development of metabolic flux models from pathway databases, and to use pathway information to leverage the interpretation of high-throughput data sets. Results In the past 4 years we have enhanced the already extensive Pathway Tools software in several respects. It can now support metabolic-model execution through the Web, it provides a more accurate gap filler for metabolic models; it supports development of models for organism communities distributed across a spatial grid; and model results may be visualized graphically. Pathway Tools supports several new omics-data analysis tools including the Omics Dashboard, multi-pathway diagrams called pathway collages, a pathway-covering algorithm for metabolomics data analysis and an algorithm for generating mechanistic explanations of multi-omics data. We have also improved the core pathway/genome databases management capabilities of the software, providing new multi-organism search tools for organism communities, improved graphics rendering, faster performance and re-designed gene and metabolite pages. Availability The software is free for academic use; a fee is required for commercial use. See http://pathwaytools.com. Contact [email protected] Supplementary information Supplementary data are available at Briefings in Bioinformatics online. Peter D. Karp, Peter E. Midford, Richard Billington, Anamika Kothari, Markus Krummenacker, Mario Latendresse, Wai Kit Ong, Pallavi Subhraveti, Ron Caspi, Carol A. Fulcher, Ingrid M. Keseler, Suzanne M. Paley |
Briefings Bioinform. | 5 |
| 2019 | The BioCyc collection of microbial genomes and metabolic pathwaysabstractBioCyc.org is a microbial genome Web portal that combines thousands of genomes with additional information inferred by computer programs, imported from other databases and curated from the biomedical literature by biologist curators. BioCyc also provides an extensive range of query tools, visualization services and analysis software. Recent advances in BioCyc include an expansion in the content of BioCyc in terms of both the number of genomes and the types of information available for each genome; an expansion in the amount of curated content within BioCyc; and new developments in the BioCyc software tools including redesigned gene/protein pages and metabolite pages; new search tools; a new sequence-alignment tool; a new tool for visualizing groups of related metabolic pathways; and a facility called SmartTables, which enables biologists to perform analyses that previously would have required a programmer's assistance. Peter D. Karp, Richard Billington, Ron Caspi, Carol A. Fulcher, Mario Latendresse, Anamika Kothari, Ingrid M. Keseler, Markus Krummenacker, Peter E. Midford, Quang Ong, Wai Kit Ong, Suzanne M. Paley, Pallavi Subhraveti |
Briefings Bioinform. | 8 |
| 2016 | Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biologyabstractPathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. Peter D. Karp, Mario Latendresse, Suzanne M. Paley, Markus Krummenacker, Quang Ong, Richard Billington, Anamika Kothari, Daniel S. Weaver, Thomas J. Lee, Pallavi Subhraveti, Aaron Spaulding, Carol A. Fulcher, Ingrid M. Keseler, Ron Caspi |
Briefings Bioinform. | 4 |
| 2016 | Representation and inference of cellular architecture for metabolic reconstruction and modelingabstractMOTIVATION: Metabolic modeling depends on accurately representing the cellular locations of enzyme-catalyzed and transport reactions. We sought to develop a representation of cellular compartmentation that would accurately capture cellular location information. We further sought a representation that would support automated inference of the cellular compartments present in newly sequenced organisms to speed model development, and that would enable representing the cellular compartments present in multiple cell types within a multicellular organism. RESULTS: We define the cellular architecture of a unicellular organism, or of a cell type from a multicellular organism, as the collection of cellular components it contains plus the topological relationships among those components. We developed a tool for inferring cellular architectures across many domains of life and extended our Cell Component Ontology to enable representation of the inferred architectures. We provide software for visualizing cellular architectures to verify their correctness and software for editing cellular architectures to modify or correct them. We also developed a representation that records the cellular compartment assignments of reactions with minimal duplication of information. AVAILABILITY AND IMPLEMENTATION: The Cell Component Ontology is freely available. The Pathway Tools software is freely available for academic research and is available for a fee for commercial use. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Suzanne M. Paley, Markus Krummenacker, Peter D. Karp |
Bioinform. | 2 |
| 2014 | Optimal metabolic route search based on atom mappingsabstractMOTIVATION: A key computational problem in metabolic engineering is finding efficient metabolic routes from a source to a target compound in genome-scale reaction networks, potentially considering the addition of new reactions. Efficiency can be based on many factors, such as route lengths, atoms conserved and the number of new reactions, and the new enzymes to catalyze them, added to the route. Fast algorithms are needed to systematically search these large genome-scale reaction networks. RESULTS: We present the algorithm used in the new RouteSearch tool within the Pathway Tools software. This algorithm is based on a general Branch-and-Bound search and involves constructing a network of atom mappings to facilitate efficient searching. As far as we know, it is the first published algorithm that finds guaranteed optimal routes where atom conservation is part of the optimality criteria. RouteSearch includes a graphical user interface that speeds user understanding of its search results. We evaluated the algorithm on five example metabolic-engineering problems from the literature; for one problem the published solution was equivalent to the optimal route found by RouteSearch; for the remaining four problems, RouteSearch found the published solution as one of its best-scored solutions. These problems were each solved in less than 5 s of computational time. AVAILABILITY AND IMPLEMENTATION: RouteSearch is accessible at BioCyc.org by using the menu command Metabolism --> Metabolic RouteSearch and by downloading Pathway Tools. Pathway Tools software is freely available to academic users, and for a fee to commercial users. Download from: http://biocyc.org/download.shtml. Mario Latendresse, Markus Krummenacker, Peter D. Karp |
Bioinform. | 2 |
| 2013 | Computing minimal nutrient sets from metabolic networks via linear constraint solvingabstractBACKGROUND: As more complete genome sequences become available, bioinformatics challenges arise in how to exploit genome sequences to make phenotypic predictions. One type of phenotypic prediction is to determine sets of compounds that will support the growth of a bacterium from the metabolic network inferred from the genome sequence of that organism. RESULTS: We present a method for computationally determining alternative growth media for an organism based on its metabolic network and transporter complement. Our method predicted 787 alternative anaerobic minimal nutrient sets for Escherichia coli K-12 MG1655 from the EcoCyc database. The program automatically partitioned the nutrients within these sets into 21 equivalence classes, most of which correspond to compounds serving as sources of carbon, nitrogen, phosphorous, and sulfur, or combinations of these essential elements. The nutrient sets were predicted with 72.5% accuracy as evaluated by comparison with 91 growth experiments. Novel aspects of our approach include (a) exhaustive consideration of all combinations of nutrients rather than assuming that all element sources can substitute for one another(an assumption that can be invalid in general) (b) leveraging the notion of a machinery-duplicating constraint, namely, that all intermediate metabolites used in active reactions must be produced in increasing concentrations to prevent successive dilution from cell division, (c) the use of Satisfiability Modulo Theory solvers rather than Linear Programming solvers, because our approach cannot be formulated as linear programming, (d) the use of Binary Decision Diagrams to produce an efficient implementation. CONCLUSIONS: Our method for generating minimal nutrient sets from the metabolic network and transporters of an organism combines linear constraint solving with binary decision diagrams to efficiently produce solution sets to provided growth problems. Steven Eker, Markus Krummenacker, Alexander Glennon Shearer, Ashish Tiwari 0001, Ingrid M. Keseler, Carolyn L. Talcott, Peter D. Karp |
BMC Bioinform. | 2 |
| 2012 | Construction and completion of flux balance models from pathway databasesabstractMOTIVATION: Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand. RESULTS: We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens. AVAILABILITY: Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Mario Latendresse, Markus Krummenacker, Miles Trupp, Peter D. Karp |
Bioinform. | 2 |
| 2010 | Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biologyabstractMOTIVATION: Biological systems function through dynamic interactions among genes and their products, regulatory circuits and metabolic networks. Our development of the Pathway Tools software was motivated by the need to construct biological knowledge resources that combine these many types of data, and that enable users to find and comprehend data of interest as quickly as possible through query and visualization tools. Further, we sought to support the development of metabolic flux models from pathway databases, and to use pathway information to leverage the interpretation of high-throughput data sets. RESULTS: In the past 4 years we have enhanced the already extensive Pathway Tools software in several respects. It can now support metabolic-model execution through the Web, it provides a more accurate gap filler for metabolic models; it supports development of models for organism communities distributed across a spatial grid; and model results may be visualized graphically. Pathway Tools supports several new omics-data analysis tools including the Omics Dashboard, multi-pathway diagrams called pathway collages, a pathway-covering algorithm for metabolomics data analysis and an algorithm for generating mechanistic explanations of multi-omics data. We have also improved the core pathway/genome databases management capabilities of the software, providing new multi-organism search tools for organism communities, improved graphics rendering, faster performance and re-designed gene and metabolite pages. AVAILABILITY: The software is free for academic use; a fee is required for commercial use. See http://pathwaytools.com. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online. Peter D. Karp, Suzanne M. Paley, Markus Krummenacker, Mario Latendresse, Joseph M. Dale, Thomas J. Lee, Pallavi Kaipa, Fred Gilham, Aaron Spaulding, Liviu Popescu, Tomer Altman, Ian T. Paulsen, Ingrid M. Keseler, Ron Caspi |
Briefings Bioinform. | 3 |
| 2005 | Querying and computing with BioCyc databasesabstractSummary: We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database. Availability: The Pathway Tools software and 20 BioCyc DBs in Tiers 1 and 2 are freely available to academic users; fees apply to some types of commercial use. For download instructions see http://BioCyc.org/download.shtml Supplementary information: For more details on programmatic access to BioCyc DBs, see http://bioinformatics.ai.sri.com/ptools/ptools-resources.html Contact: [email protected] Markus Krummenacker, Suzanne M. Paley, Lukas A. Mueller, Thomas Yan, Peter D. Karp |
Bioinform. | 1 |
| 1997 | Prediction of Enzyme Classification from Protein Sequence without the Use of Sequence Similarity
Marie desJardins, Peter D. Karp, Markus Krummenacker, Thomas J. Lee, Christos A. Ouzounis |
ISMB | 3 |