scholarly journals Modelling the Virtual Physiological Human

2011 ◽  
Vol 33 (1) ◽  
pp. 50-51
Author(s):  
Clare Sansom
Keyword(s):  
Systems Biology ◽  
Biological System ◽  
Experimental Analysis ◽  
Biological Systems ◽  
Computational Modelling ◽  
Nobel Laureate ◽  
Philosophy Of Biology ◽  
Bottom Up ◽  
Genome Projects

Systems biology – the theme of this issue of The Biochemist – can be thought of as more a philosophy of biology than a distinct set of techniques. It arose out of, but is distinct from, the genome projects and associated initiatives. The ‘catalogues’ of genes and proteins produced in recent years have generated enormous advances, but they do not tell the whole story. Nobel Laureate Sydney Brenner said in 2001 that “I know one approach that will fail, which is to start with genes, make proteins from them and try to build things bottom-up”1. In contrast with the reductionism of genomics, systems biology is ‘integrative’: as another Nobel Laureate, David Baltimore, writes, “it seeks to understand the integration of the pieces to form biological systems”2. Thus a typical systems biology study will involve both experimental analysis and computational modelling of a biological system at a number of levels: theoretically, at least, including the molecule, the pathway, the organelle, the cell, the tissue or organ, and the organism.

scholarly journals Insights from Systems Biology in Physiological Studies: Learning from Context

2017 ◽  
Vol 42 (3) ◽  
pp. 939-951
Author(s):  
Pedro Henrique Imenez Silva ◽  
Diogo Melo ◽  
Pedro Omori Ribeiro  de Mendonça
Keyword(s):  
Systems Biology ◽  
High Throughput ◽  
Biological System ◽  
Biological Systems ◽  
Experimental Studies ◽  
Holistic View ◽  
Physiological Studies ◽  
High Throughput Experiments

Systems biology presents an integrated view of biological systems, focusing on the relations between elements, whether functional or evolutionary, and providing a rich framework for the comprehension of life. At the same time, many low-throughput experimental studies are performed without influence from this integrated view, whilst high-throughput experiments use low-throughput results in their validation and interpretation. We propose an inversion in this logic, and ask which benefits could be obtained from a holistic view coming from high-throughput studies―and systems biology in particular―in interpreting and designing low-throughput experiments. By exploring some key examples from the renal and adrenal physiology, we try to show that network and modularity theory, along with observed patterns of association between elements in a biological system, can have profound effects on our ability to draw meaningful conclusions from experiments.

scholarly journals Protein–protein interactions: organization, cooperativity and mapping in a bottom-up Systems Biology approach

2005 ◽  
Vol 2 (2) ◽  
pp. S24-S35 ◽  
Author(s):  
Ozlem Keskin ◽  
Buyong Ma ◽  
Kristina Rogale ◽  
K Gunasekaran ◽  
Ruth Nussinov
Keyword(s):  
Systems Biology ◽  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Bottom Up

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.

scholarly journals Normas naturales y funciones biológicas

2013 ◽  
Author(s):  
Cristian Saborido
Keyword(s):  
Biological Function ◽  
Biological Systems ◽  
Philosophy Of Biology ◽  
Current Debate ◽  
Biological Functions ◽  
Naturalistic Account ◽  
Organizational Approach

RESUMENEn este trabajo abordo el problema de la fundamentación teórica de la noción de normatividad natural desde una perspectiva naturalista. Presento el debate actual sobre las funciones biológicas en filosofía de la biología, en el cual pueden encontrarse algunos intentos de fundamentar las normas naturales a través del concepto de función biológica. Sostengo que el enfoque predominante etiológico-evolutivo no es capaz justificar la adscripción de normas naturales en los sistemas biológicos y propongo que la nueva perspectiva organizacional está en la mejor posición para ofrecer un tratamiento naturalista de la teleología biológica y de la normatividad natural.PALABRAS CLAVENORMATIVIDAD, FUNCIÓN, NATURALISMO, TELEOLOGÍA, MALFUNCIÓN, ORGANIZACIÓNABSTRACTIn this paper I consider the problem of the theoretical grounding of the notion of natural normativity for the naturalistic perspective. I present the current debate on biological functions in philosophy of biology in which there are some attempts to ground natural norms through the notion of biological function. I argue that the mainstream account, i.e. the evolutive-etiological approach, is not able to ground the ascription of natural norms in biological systems and I defend that the new organizational approach is in the best position to offer an adequate naturalistic account for biological teleology and natural normativity.KEYWORDSNORMATIVITY, FUNCTION, NATURALISM, TELEOLOGYGY, MALFUNCTION, ORGANIZATION

Data Analysis and Interpretation in Metabolomics

2013 ◽  
pp. 1494-1521
Author(s):  
Jose M. Garcia-Manteiga
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Data Analysis ◽  
Systems Biology ◽  
Magnetic Resonance ◽  
Biological System ◽  
Analytical Techniques ◽  
Point Of View ◽  
The Other ◽  
Top Down

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

Nanotechnology-Based Studies in Systems Biology

2015 ◽  
pp. 566-580
Author(s):  
Priti Talwar ◽  
Madhumathi Manickam ◽  
Namrata Chaudhari ◽  
Palaniyandi Ravanan
Keyword(s):  
Systems Biology ◽  
Biological System ◽  
State Of The Art

In recent years, nanotechnology-based studies have been employed in the area of systems biology. The current chapter aims to give a concise view of this emergent field of research, namely nano systems biology. A large number of such studies are based on understanding surface reactivities of a biological system. Another stream of studies is focused on imaging approaches using nano systems biology. In this chapter, the authors also illustrate state-of-the-art work using these approaches in nanomedicine.

Nanotechnology-Based Studies in Systems Biology

2018 ◽  
pp. 911-926
Author(s):  
Priti Talwar ◽  
Madhumathi Manickam ◽  
Namrata Chaudhari ◽  
Palaniyandi Ravanan
Keyword(s):  
Systems Biology ◽  
Biological System ◽  
State Of The Art

In recent years, nanotechnology-based studies have been employed in the area of systems biology. The current chapter aims to give a concise view of this emergent field of research, namely nano systems biology. A large number of such studies are based on understanding surface reactivities of a biological system. Another stream of studies is focused on imaging approaches using nano systems biology. In this chapter, the authors also illustrate state-of-the-art work using these approaches in nanomedicine.

Data Analysis and Interpretation in Metabolomics

2011 ◽  
pp. 29-56
Author(s):  
Jose M. Garcia-Manteiga
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Data Analysis ◽  
Systems Biology ◽  
Magnetic Resonance ◽  
Biological System ◽  
Analytical Techniques ◽  
Point Of View ◽  
The Other ◽  
Top Down

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

Integrative Data Analysis for Biological Discovery

2011 ◽  
pp. 1058-1065
Author(s):  
Sai Moturu
Keyword(s):  
Molecular Biology ◽  
Biological System ◽  
Molecular Level ◽  
Biological Systems ◽  
Integrated Analysis ◽  
John Muir ◽  
Complex Biological System ◽  
Protein Levels ◽  
Lofty Goal ◽  
Complex Relationships

As John Muir noted, “When we try to pick out anything by itself, we find it hitched to everything else in the Universe” (Muir, 1911). In tune with Muir’s elegantly stated notion, research in molecular biology is progressing toward a systems level approach, with a goal of modeling biological systems at the molecular level. To achieve such a lofty goal, the analysis of multiple datasets is required to form a clearer picture of entire biological systems (Figure 1). Traditional molecular biology studies focus on a specific process in a complex biological system. The availability of high-throughput technologies allows us to sample tens of thousands of features of biological samples at the molecular level. Even so, these are limited to one particular view of a biological system governed by complex relationships and feedback mechanisms on a variety of levels. Integrated analysis of varied biological datasets from the genetic, translational, and protein levels promises more accurate and comprehensive results, which help discover concepts that cannot be found through separate, independent analyses. With this article, we attempt to provide a comprehensive review of the existing body of research in this domain.

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