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Evolution, Composition and Regulation of Supernumerary B Chromosomes

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ISBN: 9783038977865 / 9783038977872 Year: Pages: 254 DOI: 10.3390/books978-3-03897-787-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology
Added to DOAB on : 2019-08-28 11:21:28
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Abstract

Supernumerary B chromosomes (Bs) are dispensable genetic elements found in thousands of species of plants and animals, and some fungi. Since their discovery more than a century ago, they have been a source of puzzlement, as they only occur in some members of a population and are absent from others. When they do occur, they are often harmful, and in the absence of “selfishness”, based on mechanisms of mitotic and meiotic drive, there appears to be no obvious reason for their existence. Cytogeneticists have long wrestled with questions about the biological existence of these enigmatic elements, including their lack of any adaptive properties, apparent absence of functional genes, their origin, sequence organization, and co-evolution as nuclear parasites. Emerging new technologies are now enabling researchers to step up a gear, to look enthusiastically beyond the previous limits of the horizon, and to uncover the secrets of these “silent” chromosomes. This book provides a comprehensive guide to theoretical advancements in the field of B chromosome research in both animal and plant systems.

Keywords

repetitive elements --- RNA-Seq --- genomics --- evolution --- cytogenetics --- supernumerary elements --- extra chromosomes --- B chromosomes --- transmission --- drive --- host/parasite interaction --- supernumerary chromosomes --- karyotype evolution --- genome instability --- supernumerary chromosomes --- heterochromatin --- parent-of-origin effects --- paternal X chromosome --- maternal X chromosome --- controlling element --- teleost --- population analysis --- whole genome resequencing --- DNA copy number variation --- ribosomal DNA --- B chromosomes --- FISH (fluorescence in situ hybridisation) --- GISH (genomic in situ hybridisation) --- Prospero autumnale complex --- supernumerary chromosomal segments (SCS) evolution --- tandem repeats --- Drosophila --- supernumerary --- satellite DNA --- sSMC --- B chromosomes --- dot-like (micro) Bs --- karyotypic characteristics --- ?s --- B morphotypes --- Apodemus peninsulae --- maize B chromosome --- centromere --- inactivation --- reactivation --- de novo centromere formation --- epigenetics --- supernumerary chromosomes --- additional chromosomes --- chromosome polymorphism --- evolution --- B chromosomes --- karyotypes --- genome evolution --- interphase nucleus --- mammals --- genes --- repetitive DNA --- transcription of heterochromatin --- B chromosomes --- grasshoppers --- DNA composition --- repeat clusters --- euchromatin degradation --- microdissected DNA probes --- B chromosome --- satellite DNA --- mobile element --- organelle DNA --- chromosome evolution --- fluorescent in situ hybridization --- Orthoptera --- satellite DNA --- supernumerary chromosome --- RepeatExplorer --- supernumerary chromosomes --- B chromosomes --- next-generation sequencing --- coverage ratio analysis --- n/a --- B chromosome --- transmission --- origin --- drive --- n/a

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 / 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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Abstract

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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CC by-nc-nd (2)


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eng (2)


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2019 (2)