A systems approach to understanding root development

2006 ◽  
Vol 84 (5) ◽  
pp. 695-701 ◽  
Author(s):  
Siobhan M. Brady ◽  
Philip N. Benfey
Keyword(s):  
Systems Biology ◽  
Systems Theory ◽  
Root Development ◽  
Evolutionary Biology ◽  
Systems Approach ◽  
Process Analysis ◽  
Model Organisms ◽  
Current Status ◽  
Data Sets ◽  
Component Identification

Systems theory has been applied to process analysis in a variety of scientific disciplines from engineering to evolutionary biology. In the recent postgenomic era, the accumulation of an enormous amount of data gained from a variety of technologies has led to a revisiting of systems theory concepts. This systems biology approach has been integral in understanding a variety of processes in a number of model organisms. This review gives an overview of systems biology approaches, from component identification to modeling of networks. Various features of the root, including its development and the availability of high resolution gene expression data sets that describe root development, make the root amenable to a systems approach. The current status of systems approaches to understanding root development is reviewed.

scholarly journals mtDNAcombine: tools to combine sequences from multiple studies

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Eleanor F. Miller ◽  
Andrea Manica
Keyword(s):  
Sequence Data ◽  
Data Extraction ◽  
Bayesian Skyline Plot ◽  
Model Organisms ◽  
Data Sets ◽  
Data Handling ◽  
Online Database ◽  
Genetic Studies ◽  
Wide Range ◽  
Existing Data

Abstract Background Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms’ classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species’ demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Results Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing sequence data for Bayesian skyline plot demographic reconstructions. Conclusions There is now more genetic information available than ever before and large meta-data sets offer great opportunities to explore new and exciting avenues of research. However, compiling multi-study datasets still remains a technically challenging prospect. The mtDNAcombine package provides a pipeline to streamline the process of downloading, curating, and analysing sequence data, guiding the process of compiling data sets from the online database GenBank.

POSTPARTUM AMENORRHOEA IN RURAL EASTERN UTTAR PRADESH, INDIA

1998 ◽  
Vol 30 (2) ◽  
pp. 227-243
Author(s):  
K. N. S. YADAVA ◽  
S. K. JAIN
Keyword(s):  
Higher Education ◽  
Uttar Pradesh ◽  
Current Status Data ◽  
North India ◽  
Current Status ◽  
Data Sets ◽  
Survival Status ◽  
The Mean ◽  
The Difference ◽  
Using Data

This paper calculates the mean duration of the postpartum amenorrhoea (PPA) and examines its demographic, and socioeconomic correlates in rural north India, using data collected through 'retrospective' (last but one child) as well as 'current status' (last child) reporting of the duration of PPA.The mean duration of PPA was higher in the current status than in the retrospective data;n the difference being statistically significant. However, for the same mothers who gave PPA information in both the data sets, the difference in mean duration of PPA was not statistically significant. The correlates were identical in both the data sets. The current status data were more complete in terms of the coverage, and perhaps less distorted by reporting errors caused by recall lapse.A positive relationship of the mean duration of PPA was found with longer breast-feeding, higher parity and age of mother at the birth of the child, and the survival status of the child. An inverse relationship was found with higher education of a woman, higher education of her husband and higher socioeconomic status of her household, these variables possibly acting as proxies for women's better nutritional status.

Current status of systems biology in Aspergilli

2009 ◽  
Vol 46 (1) ◽  
pp. S180-S190 ◽  
Author(s):  
M.R. Andersen ◽  
J. Nielsen
Keyword(s):  
Systems Biology ◽  
Current Status

scholarly journals Future of Personalized Medicine in Oncology: A Systems Biology Approach

2010 ◽  
Vol 28 (16) ◽  
pp. 2777-2783 ◽  
Author(s):  
Ana Maria Gonzalez-Angulo ◽  
Bryan T.J. Hennessy ◽  
Gordon B. Mills
Keyword(s):  
Systems Biology ◽  
Patient Outcomes ◽  
Cost Effective ◽  
Molecular Medicine ◽  
Multidimensional Data ◽  
Data Sets ◽  
Therapeutic Modalities ◽  
Molecular Tests ◽  
Therapeutic Decision Making ◽  
The Masses

The development of cost-effective technologies able to comprehensively assess DNA, RNA, protein, and metabolites in patient tumors has fueled efforts to tailor medical care. Indeed validated molecular tests assessing tumor tissue or patient germline DNA already drive therapeutic decision making. However, many theoretical and regulatory challenges must still be overcome before fully realizing the promise of personalized molecular medicine. The masses of data generated by high-throughput technologies are challenging to manage, visualize, and convert to the knowledge required to improve patient outcomes. Systems biology integrates engineering, physics, and mathematical approaches with biologic and medical insights in an iterative process to visualize the interconnected events within a cell that determine how inputs from the environment and the network rewiring that occurs due to the genomic aberrations acquired by patient tumors determines cellular behavior and patient outcomes. A cross-disciplinary systems biology effort will be necessary to convert the information contained in multidimensional data sets into useful biomarkers that can classify patient tumors by prognosis and response to therapeutic modalities and to identify the drivers of tumor behavior that are optimal targets for therapy. An understanding of the effects of targeted therapeutics on signaling networks and homeostatic regulatory loops will be necessary to prevent inadvertent effects as well as to develop rational combinatorial therapies. Systems biology approaches identifying molecular drivers and biomarkers will lead to the implementation of smaller, shorter, cheaper, and individualized clinical trials that will increase the success rate and hasten the implementation of effective therapies into the clinical armamentarium.

The New Statistics with R

2021 ◽  
Author(s):  
Andy Hector
Keyword(s):  
Linear Model ◽  
Evolutionary Biology ◽  
Environmental Science ◽  
Research Training ◽  
Model Analysis ◽  
Scientific Data ◽  
Information Criteria ◽  
Reproducible Research ◽  
Data Sets ◽  
R Programming

Statistics is a fundamental component of the scientific toolbox, but learning the basics of this area of mathematics is one of the most challenging parts of a research training. This book gives an up-to-date introduction to the classical techniques and modern extensions of linear-model analysis—one of the most useful approaches in the analysis of scientific data in the life and environmental sciences. The book emphasizes an estimation-based approach that takes account of recent criticisms of overuse of probability values and introduces the alternative approach using information criteria. The book is based on the use of the open-source R programming language for statistics and graphics, which is rapidly becoming the lingua franca in many areas of science. This second edition adds new chapters, including one discussing some of the complexities of linear-model analysis and another introducing reproducible research documents using the R Markdown package. Statistics is introduced through worked analyses performed in R using interesting data sets from ecology, evolutionary biology, and environmental science. The data sets and R scripts are available as supporting material.

Roles of Caenorhabditis elegans WRN Helicase in DNA Damage Responses, and a Comparison with Its Mammalian Homolog: A Mini-Review

Gerontology ◽  
2015 ◽  
Vol 62 (3) ◽  
pp. 296-303 ◽  
Author(s):  
Jin-Sun Ryu ◽  
Hyeon-Sook Koo
Keyword(s):  
Dna Damage ◽  
Caenorhabditis Elegans ◽  
Werner Syndrome ◽  
Model Organisms ◽  
Current Status ◽  
Helicase Domain ◽  
Replication Forks ◽  
Dna Breaks ◽  
Double Strand Dna Breaks ◽  
Double Strand Dna

Werner syndrome protein (WRN) is unusual among RecQ family DNA helicases in having an additional exonuclease activity. WRN is involved in the repair of double-strand DNA breaks via the homologous recombination and nonhomologous end joining pathways, and also in the base excision repair pathway. In addition, the protein promotes the recovery of stalled replication forks. The helicase activity is thought to unwind DNA duplexes, thereby moving replication forks or Holliday junctions. The targets of the exonuclease could be the nascent DNA strands at a replication fork or the ends of double-strand DNA breaks. However, it is not clear which enzyme activities are essential for repairing different types of DNA damage. Model organisms such as mice, flies, and worms deficient in WRN homologs have been investigated to understand the physiological results of defects in WRN activity. Premature aging, the most remarkable characteristic of Werner syndrome, is also seen in the mutant mice and worms, and hypersensitivity to DNA damage has been observed in WRN mutants of all three model organisms, pointing to conservation of the functions of WRN. In the nematode Caenorhabditis elegans, the WRN homolog contains a helicase domain but no exonuclease domain, so that this animal is very useful for studying the in vivo functions of the helicase without interference from the activity of the exonuclease. Here, we review the current status of investigations of C. elegans WRN-1 and discuss its functional differences from the mammalian homologs.

The end of “naïve reductionism”: rise of systems biology or renaissance of physiology?

2005 ◽  
Vol 288 (5) ◽  
pp. C968-C974 ◽  
Author(s):  
Kevin Strange
Keyword(s):  
Systems Biology ◽  
Common Ground ◽  
Academic Discipline ◽  
Model Organisms ◽  
Interacting Proteins ◽  
Comprehensive Understanding ◽  
Research And Teaching ◽  
Real Risk ◽  
Essential Components ◽  
Teaching Programs

Systems biology is an emerging discipline focused on tackling the enormous intellectual and technical challenges associated with translating genome sequence into a comprehensive understanding of how organisms are built and run. Physiology and systems biology share the goal of understanding the integrated function of complex, multicomponent biological systems ranging from interacting proteins that carry out specific tasks to whole organisms. Despite this common ground, physiology as an academic discipline runs the real risk of fading into the background and being superseded organizationally and administratively by systems biology. My goal in this article is to discuss briefly the cornerstones of modern systems biology, specifically functional genomics, nonmammalian model organisms and computational biology, and to emphasize the need to embrace them as essential components of 21st-century physiology departments and research and teaching programs.

A Systems Approach to the Design and Development of Interactive Videodisc Training

1989 ◽  
Vol 17 (4) ◽  
pp. 255-271 ◽  
Author(s):  
Jeffrey A. Cantor
Keyword(s):  
Formative Evaluation ◽  
Systems Approach ◽  
System Development ◽  
Process Analysis ◽  
Evaluation Process ◽  
Interactive Videodisc ◽  
Systematic Design ◽  
Design And Development ◽  
Test And Evaluation ◽  
Instructional Product

This article describes a four-phased process used by the U.S. Navy for the systematic design and development of interactive videodisc (IVD) courseware (ICW). Phase One of the process, Analysis and Alternatives, describes the methodology for analyzing job/task data for the purpose of verifying the appropriateness of interactive videodisc as the medium of instructional choice, and for analyzing the proposed problem, and scoping out the approach and solution. Phase Two, System Design, describes the process for the layout and design of the IVD instructional product. Phase Three, System Development, discusses the process followed to actually develop and construct an IVD system. Lastly, Phase Four, System Test and Evaluation, will describe the formative evaluation process through which the IVD product and system is proven ready for use.

scholarly journals Efficient detection of repeating sites to accelerate phylogenetic likelihood calculations

2016 ◽  
Author(s):  
Kassian Kobert ◽  
Alexandros Stamatakis ◽  
Tomáš Flouri
Keyword(s):  
Evolutionary Biology ◽  
Likelihood Function ◽  
Simulated Data ◽  
Evolutionary Model ◽  
Identical Result ◽  
Model Parameters ◽  
Data Sets ◽  
Efficient Detection ◽  
Novel Method ◽  
Computational Bottleneck

The phylogenetic likelihood function is the major computational bottleneck in several applications of evolutionary biology such as phylogenetic inference, species delimitation, model selection and divergence times estimation. Given the alignment, a tree and the evolutionary model parameters, the likelihood function computes the conditional likelihood vectors for every node of the tree. Vector entries for which all input data are identical result in redundant likelihood operations which, in turn, yield identical conditional values. Such operations can be omitted for improving run-time and, using appropriate data structures, reducing memory usage. We present a fast, novel method for identifying and omitting such redundant operations in phylogenetic likelihood calculations, and assess the performance improvement and memory saving attained by our method. Using empirical and simulated data sets, we show that a prototype implementation of our method yields up to 10-fold speedups and uses up to 78% less memory than one of the fastest and most highly tuned implementations of the phylogenetic likelihood function currently available. Our method is generic and can seamlessly be integrated into any phylogenetic likelihood implementation.

scholarly journals The Power and Promise of Developmental Systems Theory

2018 ◽  
Vol 3 (2) ◽  
pp. 88-103 ◽  
Author(s):  
Letitia Meynell
Keyword(s):  
Systems Theory ◽  
Evolutionary Biology ◽  
Developmental Systems Theory ◽  
Developmental Systems ◽  
Political Theories

I argue that it is time for many feminists to rethink their attitudes towards evolutionary biology, not because feminists have been wrong to be deeply sceptical about many of its claims, both explicit and implicit, but because biology itself has changed. A new appreciation for the importance of development in biology has become mainstream and a new ontology, associated with developmental systems theory (DST), has been introduced over the last two decades. This turn challenges some of the features of evolutionary biology that have most troubled feminists. DST undermines the idea of biological essences and challenges both nature/nurture and nature/culture distinctions. Freed from these conceptual constraints, evolutionary biology no longer poses the problems that have justified feminist scepticism. Indeed, feminists have already found useful applications for DST and I argue that they should expand their use of DST to support more radical and wide-ranging political theories.

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