Lecture

Metabolic Modeling: Data Integration

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

ChE-411: Principles and applications of systems biology

The course introduces and develops the key concepts from systems biology and systems engineering in the context of complex biological networks. The lectures elaborate on techniques and methods to model and analyze complex biological problems. ...

Description

This lecture covers the process of genome-scale model reconstruction, functional annotation, and data integration for metabolic modeling. It includes steps such as manual curation, collecting organism-specific data, and integrating experimental data. The lecture also discusses the simulation of metabolism, reaction mechanisms, and the design of metabolic engineering strategies.

Instructor

Vassily Hatzimanikatis

Dr. Vassily Hatzimanikatis is currently Associate Professor of Chemical Engineering and Bioengineering at Ecole Polytechnique Federale de Lausanne (EPFL), in Lausanne, Switzerland. Vassily received a PhD and an MS in Chemical Engineering from the California Institute of Technology, and his Diploma in Chemical Engineering from the University of Patras, in Greece. After the completion of his doctoral studies, he held a research group leader position at the Swiss Federal Institute of Technology in Zurich (ETHZ), Switzerland. Prior to joining EPFL, Vassily worked for three years in DuPont, Cargill, and Cargill Dow, and he has been assistant professor at Northwestern University, at Illinois, USA. Vassilys research interests are in the areas of computational systems biology, biotechnology, and complexity. He is associate editor of the journals Biotechnology & Bioengineering, Metabolic Engineering and Integrative Biology, and he serves on the editorial advisory board of the journals Bioprocess and Biosystems Engineering, Journal of Chemical Technology and Biotechnology, and Industrial Biotechnology. He has written over 70 technical publications and he is co-inventor in three patents and patent applications. Vassily is a fellow of the American Institute for Medical and Biological Engineering (2010), he was a DuPont Young Professor (2001-2004), and he has also received the Jay Bailey Young Investigator Award in Metabolic Engineering (2000), and the ACS Elmar Gaden Award (2011).

Official source

Related concepts (31)

Metabolic network modelling

Metabolic network modelling, also known as metabolic network reconstruction or metabolic pathway analysis, allows for an in-depth insight into the molecular mechanisms of a particular organism. In particular, these models correlate the genome with molecular physiology. A reconstruction breaks down metabolic pathways (such as glycolysis and the citric acid cycle) into their respective reactions and enzymes, and analyzes them within the perspective of the entire network.

Metabolic pathway

In biochemistry, a metabolic pathway is a linked series of chemical reactions occurring within a cell. The reactants, products, and intermediates of an enzymatic reaction are known as metabolites, which are modified by a sequence of chemical reactions catalyzed by enzymes. In most cases of a metabolic pathway, the product of one enzyme acts as the substrate for the next. However, side products are considered waste and removed from the cell. These enzymes often require dietary minerals, vitamins, and other cofactors to function.

Thermodynamics

Thermodynamics is a branch of physics that deals with heat, work, and temperature, and their relation to energy, entropy, and the physical properties of matter and radiation. The behavior of these quantities is governed by the four laws of thermodynamics which convey a quantitative description using measurable macroscopic physical quantities, but may be explained in terms of microscopic constituents by statistical mechanics.

Transcriptomics technologies

Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell.

Laws of thermodynamics

The laws of thermodynamics are a set of scientific laws which define a group of physical quantities, such as temperature, energy, and entropy, that characterize thermodynamic systems in thermodynamic equilibrium. The laws also use various parameters for thermodynamic processes, such as thermodynamic work and heat, and establish relationships between them. They state empirical facts that form a basis of precluding the possibility of certain phenomena, such as perpetual motion.

Related lectures (64)

Systems Biology: Warburg Effect

Explores the Warburg Effect in cancer cells, discussing metabolic shifts and kinetic model construction.

Metabolic Flux Balance Analysis

Covers modeling and analyzing complex biological networks, focusing on metabolism and signaling, using techniques like flux balance analysis and kinetic modeling.

Flux Balance Analysis: Optimization and Phenotypic Phase Planes

Explores Flux Balance Analysis principles, optimization, Phenotypic Phase Planes, and bioenergetics in metabolic networks.

Metabolic Modeling: TFA and Kinetic Models

Explores metabolic modeling using TFA and kinetic models, covering growth simulation, nutrient trade-offs, phenotypic analysis, and metabolomics integration.

Thermodynamics in Metabolic Pathways