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Almut Heinken

dblp:236/0736 · DBLP profile ↗
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4ranked-venue papers
2as first author
3since 2021 · last 2023
0000-0001-6938-8072ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 4 · 2 first-author · 3 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
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 biology
metabolic network reconstruction
0.512021
DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations · Bioinform. 2021
Bioinformatics and computational biology › systems biology
constraint-based modeling
0.412019
The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities · Bioinform. 2019
Bioinformatics and computational biology › systems biology
metabolic network modeling
0.412019
The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities · Bioinform. 2019
Bioinformatics and computational biology
metagenomics
0.412019
The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities · Bioinform. 2019
Bioinformatics and computational biology › computational microbiology › microbiome analysis
microbial community modeling
0.412019
The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities · Bioinform. 2019

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

constraint-based reconstruction and analysis · 1.5
YearPublicationVenuePosition
2023 A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia
abstract
Harnessing the power of microbial consortia is integral to a diverse range of sectors, from healthcare to biotechnology to environmental remediation. To fully realize this potential, it is critical to understand the mechanisms behind the interactions that structure microbial consortia and determine their functions. Constraint-based reconstruction and analysis (COBRA) approaches, employing genome-scale metabolic models (GEMs), have emerged as the state-of-the-art tool to simulate the behavior of microbial communities from their constituent genomes. In the last decade, many tools have been developed that use COBRA approaches to simulate multi-species consortia, under either steady-state, dynamic, or spatiotemporally varying scenarios. Yet, these tools have not been systematically evaluated regarding their software quality, most suitable application, and predictive power. Hence, it is uncertain which tools users should apply to their system and what are the most urgent directions that developers should take in the future to improve existing capacities. This study conducted a systematic evaluation of COBRA-based tools for microbial communities using datasets from two-member communities as test cases. First, we performed a qualitative assessment in which we evaluated 24 published tools based on a list of FAIR (Findability, Accessibility, Interoperability, and Reusability) features essential for software quality. Next, we quantitatively tested the predictions in a subset of 14 of these tools against experimental data from three different case studies: a) syngas fermentation by C. autoethanogenum and C. kluyveri for the static tools, b) glucose/xylose fermentation with engineered E. coli and S. cerevisiae for the dynamic tools, and c) a Petri dish of E. coli and S. enterica for tools incorporating spatiotemporal variation. Our results show varying performance levels of the best qualitatively assessed tools when examining the different categories of tools. The differences in the mathematical formulation of the approaches and their relation to the results were also discussed. Ultimately, we provide recommendations for refining future GEM microbial modeling tools.
William T. Scott Jr., Sara Benito-Vaquerizo, Johannes Zimmermann, Djordje Bajic, Almut Heinken, María Suárez-Diez, Peter J. Schaap
PLoS Comput. Biol.5
2022 Microbiome Modelling Toolbox 2.0: efficient, tractable modelling of microbiome communities
abstract
MOTIVATION: Constraint-Based Reconstruction and Analysis (COBRA) is a widely used approach for the interrogation and stratification of microbiome samples, yet applications to large-scale cohorts are hampered by limited scalability and efficiency of simulations. RESULTS: We substantially improved the computation speed and scalability of a previous implementation for the construction and interrogation of personalized constraint-based microbiome models as well as implemented additional functionalities for analysis and visualization. AVAILABILITY AND IMPLEMENTATION: Microbiome Modelling Toolbox and tutorials are freely available as part of the COBRA Toolbox at https://git.io/microbiomeModelingToolbox.
Almut Heinken, Ines Thiele
Bioinform.1
2021 DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations
abstract
Abstract Motivation Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account. Results We developed Data-drivEn METabolic nEtwork Refinement (DEMETER), a Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension, which enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data and refinement of pathways based on manually refined genome annotations. Availability and implementation DEMETER and tutorials are freely available at https://github.com/opencobra. Supplementary information Supplementary data are available at Bioinformatics online.
Almut Heinken, Stefanía Magnúsdóttir, Ronan M. T. Fleming, Ines Thiele
Bioinform.1
2019 The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities
abstract
MOTIVATION: The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. RESULTS: To address this gap, we created a comprehensive toolbox to model (i) microbe-microbe and host-microbe metabolic interactions, and (ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the constraint-based reconstruction and analysis toolbox. AVAILABILITY AND IMPLEMENTATION: The Microbiome Modeling Toolbox and the tutorials at https://git.io/microbiomeModelingToolbox.
Federico Baldini, Almut Heinken, Laurent Heirendt, Stefanía Magnúsdóttir, Ronan M. T. Fleming, Ines Thiele
Bioinform.2