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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

Dose-Time relationship --- Network inference --- Multiple omics --- Data integration --- Visualization

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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

Multisource heterogenous omics --- cancer --- computational cancer biology --- genetic --- epigenetic --- data integration --- multi-omics --- genome-wide studies ---  omics data

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The history of livestock started with the domestication of their wild ancestors: a restricted number of species allowed to be tamed and entered a symbiotic relationship with humans. In exchange for food, shelter and protection, they provided us with meat, eggs, hides, wool and draught power, thus contributing considerably to our economic and cultural development. Depending on the species, domestication took place in different areas and periods. After domestication, livestock spread over all inhabited regions of the earth, accompanying human migrations and becoming also trade objects. This required an adaptation to different climates and varying styles of husbandry and resulted in an enormous phenotypic diversity. Approximately 200 years ago, the situation started to change with the rise of the concept of breed. Animals were selected for the same visible characteristics, and crossing with different phenotypes was reduced. This resulted in the formation of different breeds, mostly genetically isolated from other populations. A few decades ago, selection pressure was increased again with intensive production focusing on a limited range of types and a subsequent loss of genetic diversity. For short-term economic reasons, farmers have abandoned traditional breeds. As a consequence, during the 20th century, at least 28% of farm animal breeds became extinct, rare or endangered. The situation is alarming in developing countries, where native breeds adapted to local environments and diseases are being replaced by industrial breeds. In the most marginal areas, farm animals are considered to be essential for viable land use and, in the developing world, a major pathway out of poverty. Historic documentation from the period before the breed formation is scarce. Thus, reconstruction of the history of livestock populations depends on archaeological, archeo-zoological and DNA analysis of extant populations. Scientific research into genetic diversity takes advantage of the rapid advances in molecular genetics. Studies of mitochondrial DNA, microsatellite DNA profiling and Y-chromosomes have revealed details on the process of domestication, on the diversity retained by breeds and on relationships between breeds. However, we only see a small part of the genetic information and the advent of new technologies is most timely in order to answer many essential questions. High-throughput single-nucleotide polymorphism genotyping is about to be available for all major farm animal species. The recent development of sequencing techniques calls for new methods of data management and analysis and for new ideas for the extraction of information. To make sense of this information in practical conditions, integration of geo-environmental and socio-economic data are key elements. The study and management of farm animal genomic resources (FAnGR) is indeed a major multidisciplinary issue.The goal of the present Research Topic is to collect contributions of high scientific quality relevant to biodiversity management, and applying new methods to either new genomic and bioinformatics approaches for characterization of FAnGR, to the development of FAnGR conservation methods applied ex-situ and in-situ, to socio-economic aspects of FAnGR conservation, to transfer of lessons between wildlife and livestock biodiversity conservation, and to the contribution of FAnGR to a transition in agriculture (FAnGR and agro-ecology).

Cattle --- Livestock --- Biodiversity. --- Genetics. --- Genome mapping. --- Conservation. --- GIS --- Decision Making --- Farm animal genomic resources (FAnGR) --- Social Sciences --- Disease Resistance --- next generation sequencing --- conservation of genomic diversity --- data integration --- sustainable breeding --- Polygenic adaptive and economic traits

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This book entitled Marine Algal Antioxidants, as a special issue of the Antioxidants journal, encloses eleven scientific articles with a preface written by the two editors, Christophe Brunet and Clementina Sansone. Marine Algal Antioxidants book reports advances of the research on marine photosynthetic organisms for the growth of biotechnological pipelines aimed to enhance antioxidant molecules production by algae. More than twenty scientists share the results of their research and highlight the relevance of algae for developing marine biotechnology products to flourish the requirements of nutraceuticals or cosmeceuticals in the defense of human health. Multidisciplinarity of the scientific approaches presented in this book – such as physiological, molecular, chemistry, technical or technological methodologies – lays the foundation for harmonizing the links between them towards the unique goal of the improvement of marine algal factory processes.

algae --- Chlorella --- Fucus --- detoxification --- environmental pollution --- antioxidants --- heavy metals --- selenium --- SOD-1 --- neurotoxicology --- aminoazuphrates --- clinical medicine --- nutrition --- neuropathology --- Dunaliella salina --- microalgae --- red LED --- blue LED --- growth --- carotenoids --- plastoquinol:oxygen oxidoreductase --- photosynthesis --- antioxidant activities --- Box–Behnken design --- microwave-assisted extraction --- polysaccharide --- Ulva pertusa --- seaweed --- 9-cis β-carotene --- all-trans β-carotene --- light intensity --- isomerisation --- light --- ascorbic acid --- phenolic compounds --- flavonoids --- photoprotection --- Phaeodactylum tricornutum --- fucoxanthin --- antioxidative --- antiproliferative --- antioxidant --- biodiversity --- genome–scale metabolic networks (GSMNs), data integration --- brown algae --- oxygenated carotenoid biosynthesis --- abscisic acid --- Saccharina japonica --- Cladosiphon okamuranus --- lipophilic antioxidant --- solvent blending --- macroalgae --- LC-ESI-MS/MS --- carotenoid pigment --- anthocyanin --- chlorophyll derivative --- phototrophic --- heterotrophic --- Scenedesmus --- chlorophylls --- hydroxy-chlorophyll --- oxidative metabolism --- ROS --- lactone-chlorophyll --- photoacclimation --- seaweeds --- green algae --- marine algae --- Ulva intestinalis --- Enteromorpha intestinalis --- quantification --- polyphenols --- apigenin --- accelerated solvent extraction --- ASE --- HPLC-LRMS --- HPLC-HRMS --- HPLC --- TPC --- Folin–Ciocalteu --- TFC --- qNMR --- n/a --- Box-Behnken design --- genome-scale metabolic networks (GSMNs), data integration --- Folin-Ciocalteu

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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.

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