TY - JOUR

T1 - MAMMOTh

T2 - A new database for curated mathematical models of biomolecular systems

AU - Kazantsev, Fedor

AU - Akberdin, Ilya

AU - Lashin, Sergey

AU - Ree, Natalia

AU - Timonov, Vladimir

AU - Ratushny, Alexander

AU - Khlebodarova, Tamara

AU - Likhoshvai, Vitaly

N1 - Publisher Copyright: © 2018 World Scientific Publishing Europe Ltd.

PY - 2018/2/1

Y1 - 2018/2/1

N2 - Motivation: Living systems have a complex hierarchical organization that can be viewed as a set of dynamically interacting subsystems. Thus, to simulate the internal nature and dynamics of the entire biological system, we should use the iterative way for a model reconstruction, which is a consistent composition and combination of its elementary subsystems. In accordance with this bottom-up approach, we have developed the MAthematical Models of bioMOlecular sysTems (MAMMOTh) tool that consists of the database containing manually curated MAMMOTh fitted to the experimental data and a software tool that provides their further integration. Results: The MAMMOTh database entries are organized as building blocks in a way that the model parts can be used in different combinations to describe systems with higher organizational level (metabolic pathways and/or transcription regulatory networks). The tool supports export of a single model or their combinations in SBML or Mathematica standards. The database currently contains 110 mathematical sub-models for Escherichia coli elementary subsystems (enzymatic reactions and gene expression regulatory processes) that can be combined in at least 5100 complex/sophisticated models concerning more complex biological processes as de novo nucleotide biosynthesis, aerobic/anaerobic respiration and nitrate/nitrite utilization in E. Coli. All models are functionally interconnected and sufficiently complement public model resources. Availability: http://mammoth.biomodelsgroup.ru.

AB - Motivation: Living systems have a complex hierarchical organization that can be viewed as a set of dynamically interacting subsystems. Thus, to simulate the internal nature and dynamics of the entire biological system, we should use the iterative way for a model reconstruction, which is a consistent composition and combination of its elementary subsystems. In accordance with this bottom-up approach, we have developed the MAthematical Models of bioMOlecular sysTems (MAMMOTh) tool that consists of the database containing manually curated MAMMOTh fitted to the experimental data and a software tool that provides their further integration. Results: The MAMMOTh database entries are organized as building blocks in a way that the model parts can be used in different combinations to describe systems with higher organizational level (metabolic pathways and/or transcription regulatory networks). The tool supports export of a single model or their combinations in SBML or Mathematica standards. The database currently contains 110 mathematical sub-models for Escherichia coli elementary subsystems (enzymatic reactions and gene expression regulatory processes) that can be combined in at least 5100 complex/sophisticated models concerning more complex biological processes as de novo nucleotide biosynthesis, aerobic/anaerobic respiration and nitrate/nitrite utilization in E. Coli. All models are functionally interconnected and sufficiently complement public model resources. Availability: http://mammoth.biomodelsgroup.ru.

KW - de novo nucleotide synthesis

KW - gene expression

KW - gene network

KW - generalized Hill functions

KW - Mathematical models

KW - respiration

KW - METABOLISM

KW - NETWORK MOTIFS

KW - BIOLOGY

KW - ALGORITHMS

KW - Models, Theoretical

KW - Escherichia coli/genetics

KW - Gene Regulatory Networks

KW - Metabolic Networks and Pathways

KW - Software

KW - Databases, Factual

UR - http://www.scopus.com/inward/record.url?scp=85044283745&partnerID=8YFLogxK

U2 - 10.1142/S0219720017400108

DO - 10.1142/S0219720017400108

M3 - Article

C2 - 29172865

AN - SCOPUS:85044283745

VL - 16

JO - Journal of Bioinformatics and Computational Biology

JF - Journal of Bioinformatics and Computational Biology

SN - 0219-7200

IS - 1

M1 - 1740010

ER -