scholarly journals Understanding diseases by mouse click: the promise and potential of computational approaches in Systems Biology

2007 ◽  
Vol 149 (3) ◽  
pp. 424-429 ◽  
Author(s):  
F. Klauschen ◽  
B. R. Angermann ◽  
M. Meier-Schellersheim
2012 ◽  
Vol 23 (4) ◽  
pp. 609-616 ◽  
Author(s):  
Murat Iskar ◽  
Georg Zeller ◽  
Xing-Ming Zhao ◽  
Vera van Noort ◽  
Peer Bork

2007 ◽  
Vol 4 (3) ◽  
pp. 252-263 ◽  
Author(s):  
Allyson L. Lister ◽  
Matthew Pocock ◽  
Anil Wipat

Abstract The creation of quantitative, simulatable, Systems Biology Markup Language (SBML) models that accurately simulate the system under study is a time-intensive manual process that requires careful checking. Currently, the rules and constraints of model creation, curation, and annotation are distributed over at least three separate documents: the SBML schema document (XSD), the Systems Biology Ontology (SBO), and the “Structures and Facilities for Model Definition” document. The latter document contains the richest set of constraints on models, and yet it is not amenable to computational processing. We have developed a Web Ontology Language (OWL) knowledge base that integrates these three structure documents, and that contains a representative sample of the information contained within them. This Model Format OWL (MFO) performs both structural and constraint integration and can be reasoned over and validated. SBML Models are represented as individuals of OWL classes, resulting in a single computationally amenable resource for model checking. Knowledge that was only accessible to humans is now explicitly and directly available for computational approaches. The integration of all structural knowledge for SBML models into a single resource creates a new style of model development and checking.


Author(s):  
Yun Zhang ◽  
F.N. Abu-Khzam ◽  
N.E. Baldwin ◽  
E.J. Chesler ◽  
M.A. Langston ◽  
...  

2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
Gavin C. Bowick ◽  
Alan D. T. Barrett

Developing vaccines to biothreat agents presents a number of challenges for discovery, preclinical development, and licensure. The need for high containment to work with live agents limits the amount and types of research that can be done using complete pathogens, and small markets reduce potential returns for industry. However, a number of tools, from comparative pathogenesis of viral strains at the molecular level to novel computational approaches, are being used to understand the basis of viral attenuation and characterize protective immune responses. As the amount of basic molecular knowledge grows, we will be able to take advantage of these tools not only to rationally attenuate virus strains for candidate vaccines, but also to assess immunogenicity and safety in silico. This review discusses how a basic understanding of pathogenesis, allied with systems biology and machine learning methods, can impact biodefense vaccinology.


2011 ◽  
Vol 286 (27) ◽  
pp. 23653-23658 ◽  
Author(s):  
Hon Nian Chua ◽  
Frederick P. Roth

Computational systems biology is empowering the study of drug action. Studies on biological effects of chemical compounds have increased in scale and accessibility, allowing integration with other large-scale experimental data types. Here, we review computational approaches for elucidating the mechanisms of both intended and undesirable effects of drugs, with the collective potential to change the nature of drug discovery and pharmacological therapy.


2021 ◽  
pp. 1-19
Author(s):  
Connor Seeley ◽  
Kimberly B. Kegel-Gleason

Mass spectrometry (MS) is a physical technique used to identify specific chemicals and molecules by precise analysis of their mass and charge; this technology has been adapted for biological sciences applications. Investigators have used MS to identify differential expressions of proteins in Huntington’s disease (HD), to discover Huntingtin (HTT) interacting proteins and to analyze HTT proteoforms. Using systems biology and computational approaches, data from MS screens have been leveraged to find differentially expressed pathways. This review summarizes the data from most of the MS studies done in the HD field in the last 20 years and compares it to the protein data reported before the use of MS technology. The MS results validate early findings in the field such as differential expression of PDE10a and DARPP-32 and identify new changes. We offer a perspective on the MS approach in HD, particularly for identification of disease pathways, the challenges in interpreting data across different studies, and its application to protein studies moving forward.


Biomolecules ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1245 ◽  
Author(s):  
Fotis A. Baltoumas ◽  
Sofia Zafeiropoulou ◽  
Evangelos Karatzas ◽  
Mikaela Koutrouli ◽  
Foteini Thanati ◽  
...  

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.


2008 ◽  
Vol 36 (1) ◽  
pp. 51-54 ◽  
Author(s):  
Matthias Stein ◽  
Razif R. Gabdoulline ◽  
Rebecca C. Wade

Enzyme kinetic parameters can differ between different species and isoenzymes for the same catalysed reaction. Computational approaches to calculate enzymatic kinetic parameters from the three-dimensional structures of proteins will be reviewed briefly here. Enzyme kinetic parameters may be derived by modelling and simulating the rate-determining process. An alternative, approximate, but more computationally efficient approach is the comparison of molecular interaction fields for experimentally characterized enzymes and those for which parameters should be determined. A correlation between differences in interaction fields and experimentally determined kinetic parameters can be used to determine parameters for orthologous enzymes from other species. The estimation of enzymatic kinetic parameters is an important step in setting up mathematical models of biochemical pathways in systems biology.


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