FUZZY CAUSAL MAPPING (F-CMAP) — A PROPOSAL TO DEVELOP A NEW SYSTEMS BIOLOGY TOOL

2010 ◽  
Vol 06 (01) ◽  
pp. 97-107
Author(s):  
GABRIEL WEINREB ◽  
PAUL Y. CAO
Keyword(s):  
Systems Biology ◽  
Numerical Methods ◽  
Biological Systems ◽  
General System ◽  
Linguistic Variables ◽  
System Description ◽  
Causal Mapping ◽  
Cortical Oscillations ◽  
Intuitive Manner ◽  
Biological Robustness

Biological systems are complex, consisting of many elements of different nature. As a whole, they are robust, and a general system description can be done in a semi-quantitative way when it comes to phenotype behaviors. We used these properties earlier1 to develop a new systems biology method, causal mapping (CMAP). In this paper, we pinpoint some problems with the earlier version of CMAP, and develop it further. CMAP used linguistic variables (LV) to describe the behaviour of biological systems, and here we use the procedure of fuzzyfications to improve CMAP. The numerical methods to calculate the ranges of LV are agreeable to reality in a very intuitive manner. The new version of CMAP reproduced the physical data on cortical oscillations2 in spreading cells with depolymerized microtubules. Further, predictions were made on the dependency of the myosin activity on the period of oscillations. The presented development lies on the way to a more general approach that should be able to address questions of biological robustness, modularity and hierarchy.

scholarly journals Modeling Biological Systems Using Crowdsourcing

2018 ◽  
Vol 43 (3) ◽  
pp. 219-243 ◽  
Author(s):  
Szymon Wasik
Keyword(s):  
Systems Biology ◽  
Serious Games ◽  
Domain Knowledge ◽  
Biological Systems ◽  
Effective Technique ◽  
Design Models ◽  
Modeling Systems ◽  
Vast Network

Abstract Crowdsourcing is a very effective technique for outsourcing work to a vast network usually comprising anonymous people. In this study, we review the application of crowdsourcing to modeling systems originating from systems biology. We consider a variety of verified approaches, including well-known projects such as EyeWire, FoldIt, and DREAM Challenges, as well as novel projects conducted at the European Center for Bioinformatics and Genomics. The latter projects utilized crowdsourced serious games to design models of dynamic biological systems, and it was demonstrated that these models could be used successfully to involve players without domain knowledge. We conclude the review of these systems by providing 10 guidelines to facilitate the efficient use of crowdsourcing.

7. The lawless pursuit of biological systems

2020 ◽  
pp. 108-122
Author(s):  
Eberhard O. Voit
Keyword(s):  
Systems Biology ◽  
Biological Systems ◽  
Large Classes ◽  
The Future

The laws of physics are a prerequisite for us to make reliable predictions regarding our surroundings. By extension, making reliable predictions in biology requires laws of biology. The problem is that such laws are almost non-existent, because biological systems are hugely complex and diverse. As a consequence, it is difficult to make true statements covering all organisms on Earth—or even large classes of organisms. This difficulty translates directly into the challenge of identifying rules that govern biological systems. What would such biological rules or laws even look like? ‘The lawless pursuit of biological systems’ considers the future of systems biology and discusses how it might evolve as it matures as a field of investigation.

scholarly journals Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community

Metabolites ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 76 ◽  
Author(s):  
Farhana R. Pinu ◽  
David J. Beale ◽  
Amy M. Paten ◽  
Konstantinos Kouremenos ◽  
Sanjay Swarup ◽  
...  
Keyword(s):  
New Zealand ◽  
Systems Biology ◽  
Life Science ◽  
Biological Systems ◽  
Research Community ◽  
Data Sets ◽  
Omics Data ◽  
Omics Integration ◽  
Traditional Approaches ◽  
Multiple Interactions

The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science. Omics techniques provide a more holistic molecular perspective of studied biological systems compared to traditional approaches. However, due to their inherent data differences, integrating multiple omics platforms remains an ongoing challenge for many researchers. As metabolites represent the downstream products of multiple interactions between genes, transcripts, and proteins, metabolomics, the tools and approaches routinely used in this field could assist with the integration of these complex multi-omics data sets. The question is, how? Here we provide some answers (in terms of methods, software tools and databases) along with a variety of recommendations and a list of continuing challenges as identified during a peer session on multi-omics integration that was held at the recent ‘Australian and New Zealand Metabolomics Conference’ (ANZMET 2018) in Auckland, New Zealand (Sept. 2018). We envisage that this document will serve as a guide to metabolomics researchers and other members of the community wishing to perform multi-omics studies. We also believe that these ideas may allow the full promise of integrated multi-omics research and, ultimately, of systems biology to be realized.

scholarly journals Systems Biology and Design of Biological Systems

2006 ◽  
Vol 46 (5) ◽  
pp. 244-250
Author(s):  
Hiroyuki KURATA
Keyword(s):  
Systems Biology ◽  
Biological Systems

scholarly journals COMPARISON OF NUMERICAL METHODS FOR THE PROBLEM ARISING IN THE GYROTRON THEORY

2005 ◽  
Vol 12 (1) ◽  
pp. 19-30 ◽  
Author(s):  
J. Cepitis ◽  
H. Kalis ◽  
A. Reinfelds
Keyword(s):  
Numerical Methods ◽  
Boundary Conditions ◽  
General System ◽  
Single Mode

There are considered some aspects for numerical solving of problem with Robin's boundary conditions arising in the gyrotron theory. The single mode case is carefully investigated. The obtained observations make possible to offer the suitable strategy for the numerical solving of the problem for general system of nonstationary gyrotron oscillations. Straipsnyje nagrinejami girotrono teorijos uždaviniu su Robino kraštine salyga kai kurie skaitinio sprendimo metodu aspektai. Atidžiai nagrinejamas vienos modos atvejis ir gauti pastebejimai leidžia sudaryti tinkama skaitinio šio uždavinio sprendimo strategija bendrajai girotrono lygčiu sistemai, aprašančiai jo nestacionarius virpesius.

scholarly journals Current systems biology approaches in hazard assessment of nanoparticles

2015 ◽  
Author(s):  
Friederike Ehrhart ◽  
Chris Evelo ◽  
Egon Willighagen
Keyword(s):  
Systems Biology ◽  
Hazard Assessment ◽  
Low Dose ◽  
Bulk Material ◽  
Common Knowledge ◽  
Biological Systems ◽  
Consumer Products ◽  
Human Environment ◽  
Current Systems ◽  
Nano Size

The amount of nanoparticles (NPs) in human environment is increasing. The main sources are the increased introduction in consumer products and air pollution (diesel exhaust). It is meanwhile common knowledge that NPs behave differently as bulk material because of their nano-size. This leads in general to a higher reactivity and some other changed properties, e.g. solubility, surface potential, conductivity, and, to different effects on biological systems. The main impacts of NPs on a cellular and organism level are meanwhile well known: release of toxic ions, increased oxidative stress, and inflammation. Beside these, there is increasing evidence that NPs, especially in low dose/long exposure scenarios, affect biological systems in a broader way, interact with drugs, and exacerbate the effects of diseases. To investigate these effects systems biology approaches are the method of choice. This review summarizes the state of the art of nanoparticle effects on cells and organisms and demonstrate the add value of systems biology investigations to NP hazard assessment.

scholarly journals Mathematical and Computational Modeling in Complex Biological Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Zhiwei Ji ◽  
Ke Yan ◽  
Wenyang Li ◽  
Haigen Hu ◽  
Xiaoliang Zhu
Keyword(s):  
Systems Biology ◽  
Computational Modeling ◽  
Cancer Progression ◽  
High Throughput ◽  
Computational Models ◽  
Molecular Mechanisms ◽  
Biological Process ◽  
Biological Systems ◽  
Complex Diseases ◽  
Modeling Approaches

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

2. Exciting new puzzles

2020 ◽  
pp. 9-26
Author(s):  
Eberhard O. Voit
Keyword(s):  
Systems Biology ◽  
Biological Systems ◽  
Knowledge Systems ◽  
Biological Molecules ◽  
P Systems ◽  
Whole Cells ◽  
Simple Systems ◽  
Computational Systems ◽  
Extract Information

Systems biologists want to understand how biological systems operate within their natural surroundings. These ‘systems’ may be whole cells, organisms, or even populations, but they are more often comprised of biological molecules and their interactions. Even seemingly simple systems in biology are complex, and often enormous amounts of information are involved. ‘Exciting new puzzles’ explains how computational systems biologists, or systems modellers, depend on mathematics and computing to extract information from available data and then piece this information together, thereby generating genuinely new insights and narrowing gaps in knowledge. Systems biology is in its infancy and the complexity of nature offers ambitious researchers truly tantalizing puzzles with potentially huge rewards and worldwide implications.

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