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Plant Phenotyping and Phenomics for Plant Breeding

Authors: --- --- --- --- et al.
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889455324 Year: Pages: 369 DOI: 10.3389/978-2-88945-532-4 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Botany
Added to DOAB on : 2019-01-23 14:53:42
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Abstract

As a consequence of the global climate change, both the reduction on yield potential and the available surface area of cultivated species will compromise the production of food needed for a constant growing population. There is consensus about the significant gap between world food consumption projected for the coming decades and the expected crop yield-improvements, which are estimated to be insufficient to meet the demand.The complexity of this scenario will challenge breeders to develop cultivars that are better adapted to adverse environmental conditions, therefore incorporating a new set of morpho-physiological and physico-chemical traits; a large number of these traits have been found to be linked to heat and drought tolerance.Currently, the only reasonable way to satisfy all these demands is through acquisition of high-dimensional phenotypic data (high-throughput phenotyping), allowing researchers with a holistic comprehension of plant responses, or ‘Phenomics’.Phenomics is still under development. This Research Topic aims to be a contribution to the progress of methodologies and analysis to help understand the performance of a genotype in a given environment.

Phenomics

Authors: ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889456079 Year: Pages: 222 DOI: 10.3389/978-2-88945-607-9 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Botany
Added to DOAB on : 2019-01-23 14:53:43
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"Phenomics" is an emerging area of research whose aspiration is the systematic measurement of the physical, physiological and biochemical traits (the phenome) belonging to a given individual or collection of individuals. Non-destructive or minimally invasive techniques allow repeated measurements across time to follow phenotypes as a function of developmental time. These longitudinal traits promise new insights into the ways in which crops respond to their environment including how they are managed.To maximize the benefit, these approaches should ideally be scalable so that large populations in multiple environments can be sampled repeatedly at reasonable cost. Thus, the development and validation of non-contact sensing technologies remains an area of intensive activity that ranges from Remote Sensing of crops within the landscape to high resolution at the subcellular level. Integration of this potentially highly dimensional data and linking it with variation at the genetic level is an ongoing challenge that promises to release the potential of both established and under-exploited crops.

Data Journeys in the Sciences

Authors: ---
ISBN: 9783030371777 Year: Pages: 412 DOI: 10.1007/978-3-030-37177-7 Language: English
Publisher: Springer Nature
Subject: Science (General)
Added to DOAB on : 2020-07-15 23:58:32
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This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research.

Systems Analytics and Integration of Big Omics Data

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ISBN: 9783039287444 / 9783039287451 Year: Pages: 202 DOI: 10.3390/books978-3-03928-745-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Therapeutics
Added to DOAB on : 2020-06-09 16:38:57
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A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.

Keywords

tissue-specific expressed genes --- transcriptome --- tissue classification --- support vector machine --- feature selection --- bioinformatics pipelines --- algorithm development for network integration --- miRNA–gene expression networks --- multiomics integration --- network topology analysis --- candidate genes --- gene–environment interactions --- logic forest --- systemic lupus erythematosus --- Gene Ontology --- KEGG pathways --- enrichment analysis --- proteomic analysis --- plot visualization --- Alzheimer’s disease --- dementia --- cognitive impairment --- neurodegeneration --- Gene Ontology --- annotation --- biocuration --- amyloid-beta --- microtubule-associated protein tau --- artificial intelligence --- genotype --- phenotype --- deep phenotype --- data integration --- genomics --- phenomics --- precision medicine informatics --- epigenetics --- chromatin modification --- sequencing --- regulatory genomics --- disease variants --- machine learning --- multi-omics --- data integration --- curse of dimensionality --- heterogeneous data --- missing data --- class imbalance --- scalability --- genomics --- pharmacogenomics --- cell lines --- database --- drug sensitivity --- data integration --- omics data --- genomics --- RNA expression --- non-omics data --- clinical data --- epidemiological data --- challenges --- integrative analytics --- joint modeling --- multivariate analysis --- multivariate causal mediation --- distance correlation --- direct effect --- indirect effect --- causal inference --- n/a

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