scholarly journals Network inference in systems biology: recent developments, challenges, and applications

2020 ◽  
Vol 63 ◽  
pp. 89-98 ◽  
Author(s):  
Michael M Saint-Antoine ◽  
Abhyudai Singh
Keyword(s):  
Systems Biology ◽  
Network Inference ◽  
Recent Developments

scholarly journals Recent Developments in Metabolomics Studies of Endophytic Fungi

2021 ◽  
Vol 8 (1) ◽  
pp. 28
Author(s):  
Kashvintha Nagarajan ◽  
Baharudin Ibrahim ◽  
Abdulkader Ahmad Bawadikji ◽  
Jun-Wei Lim ◽  
Woei-Yenn Tong ◽  
...  
Keyword(s):  
Systems Biology ◽  
Endophytic Fungi ◽  
Bioactive Metabolites ◽  
Vast Number ◽  
Chemical Complexity ◽  
Recent Developments ◽  
Scientific Attention ◽  
Increasing Trends ◽  
Analytical Tools ◽  
Insight Into

Endophytic fungi are microorganisms that colonize living plants’ tissues without causing any harm. They are known as a natural source of bioactive metabolites with diverse pharmacological functions. Many structurally different chemical metabolites were isolated from endophytic fungi. Recently, the increasing trends in human health problems and diseases have escalated the search for bioactive metabolites from endophytic fungi. The conventional bioassay-guided study is known as laborious due to chemical complexity. Thus, metabolomics studies have attracted extensive research interest owing to their potential in dealing with a vast number of metabolites. Metabolomics coupled with advanced analytical tools provides a comprehensive insight into systems biology. Despite its wide scientific attention, endophytic fungi metabolomics are relatively unexploited. This review highlights the recent developments in metabolomics studies of endophytic fungi in obtaining the global metabolites picture.

scholarly journals The Significance of an Enhanced Concept of the Organism for Medicine

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Bernd Rosslenbroich
Keyword(s):  
Systems Biology ◽  
Personalized Medicine ◽  
Basic Concept ◽  
Evolutionary Biology ◽  
Molecular Level ◽  
Human Individual ◽  
Recent Developments ◽  
Conceptual Shift ◽  
And Control ◽  
Comparative Embryology

Recent developments in evolutionary biology, comparative embryology, and systems biology suggest the necessity of a conceptual shift in the way we think about organisms. It is becoming increasingly evident that molecular and genetic processes are subject to extremely refined regulation and control by the cell and the organism, so that it becomes hard to define single molecular functions or certain genes as primary causes of specific processes. Rather, the molecular level is integrated into highly regulated networks within the respective systems. This has consequences for medical research in general, especially for the basic concept of personalized medicine or precision medicine. Here an integrative systems concept is proposed that describes the organism as a multilevel, highly flexible, adaptable, and, in this sense, autonomous basis for a human individual. The hypothesis is developed that these properties of the organism, gained from scientific observation, will gradually make it necessary to rethink the conceptual framework of physiology and pathophysiology in medicine.

scholarly journals Metabolomic systems biology of trypanosomes

Parasitology ◽  
2010 ◽  
Vol 137 (9) ◽  
pp. 1285-1290 ◽  
Author(s):  
MICHAEL P. BARRETT ◽  
BARBARA M. BAKKER ◽  
RAINER BREITLING
Keyword(s):  
Systems Biology ◽  
Biological Systems ◽  
Cellular Responses ◽  
Future Research ◽  
Metabolomic Analysis ◽  
Environmental Perturbation ◽  
Recent Developments ◽  
Systematic Identification ◽  
Metabolomics Analysis ◽  
Identification And Quantification

SUMMARYMetabolomics analysis, which aims at the systematic identification and quantification of all metabolites in biological systems, is emerging as a powerful new tool to identify biomarkers of disease, report on cellular responses to environmental perturbation, and to identify the targets of drugs. Here we discuss recent developments in metabolomic analysis, from the perspective of trypanosome research, highlighting remaining challenges and the most promising areas for future research.

scholarly journals Multi-Model and Network Inference Based on Ensemble Estimates: Avoiding the Madness of Crowds

2019 ◽  
Author(s):  
Michael P.H. Stumpf
Keyword(s):  
Systems Biology ◽  
Model Selection ◽  
Recent Progress ◽  
Network Inference ◽  
Applied Mathematics ◽  
System Model ◽  
Great Success ◽  
Computational Statistics ◽  
Inference Methods ◽  
Positive Results

AbstractRecent progress in theoretical systems biology, applied mathematics and computational statistics allows us to compare quantitatively the performance of different candidate models at describing a particular biological system. Model selection has been applied with great success to problems where a small number — typically less than 10 — of models are compared, but recently studies have started to consider thousands and even millions of candidate models. Often, however, we are left with sets of models that are compatible with the data, and then we can use ensembles of models to make predictions. These ensembles can have very desirable characteristics, but as I show here are not guaranteed to improve on individual estimators or predictors. I will show in the cases of model selection and network inference when we can trust ensembles, and when we should be cautious. The analyses suggests that the careful construction of an ensemble – choosing good predictors – is of paramount importance, more than had perhaps been realised before: merely adding different methods does not suffice. The success of ensemble network inference methods is also shown to rest on their ability to suppress false-positive results. A Jupyter notebook which allows carrying out an assessment of ensemble estimators is provided.

scholarly journals Modular assembly of dynamic models in systems biology

2021 ◽  
Author(s):  
Michael Pan ◽  
Peter J. Gawthrop ◽  
Joseph Cursons ◽  
Edmund Crampin
Keyword(s):  
Systems Biology ◽  
Large Scale ◽  
Dynamic Models ◽  
Mitogen Activated Protein Kinase ◽  
Bond Graphs ◽  
Modular Assembly ◽  
Scale Models ◽  
Mitogen Activated Protein ◽  
Recent Developments ◽  
Modular Modelling

It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two examples to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity.

scholarly journals Systems Biology Approaches-based Biomarkers Discovery for Acute Aortic Dissection

2018 ◽  
Vol 21 (5) ◽  
pp. E365-E369
Author(s):  
Qiang Huang ◽  
Yongqiang Ren ◽  
Hui Li ◽  
Youjin Qiao ◽  
Mingshan Lin
Keyword(s):  
Systems Biology ◽  
Aortic Dissection ◽  
High Throughput Screening ◽  
Acute Aortic Dissection ◽  
Cell Level ◽  
Diagnostic Biomarkers ◽  
Recent Developments ◽  
Life Threatening ◽  
Molecular Pathophysiology ◽  
Molecular Nature

Acute aortic dissection (AAD) faces great challenges in early diagnosis and effective drug treatment. Recent developments in systems biology approaches allow high-throughput screening of novel diagnostic biomarkers and potential therapeutic targets. In this review, we summarize the currently available AAD biomarkers identified in the context of genomic, transcriptomic, proteomic, and metabolic profiles, and highlight the benefits of using a combination of these findings for a better understanding of the molecular nature of this life-threatening disease. This review also provides a reference for future studies that employ a comprehensive, multiple-level approach at the single-cell level to decipher the underlying molecular pathophysiology of AAD.

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