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Application of Bioinformatics in Cancers

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ISBN: 9783039217885 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: English
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

Plant Protein and Proteome Altlas--Integrated Omics Analyses of Plants under Abiotic Stresses

Authors: --- --- --- --- et al.
ISBN: 9783039219605 / 9783039219612 Year: Pages: 558 DOI: 10.3390/books978-3-03921-961-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Botany
Added to DOAB on : 2020-06-09 16:38:57
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Abstract

Integrative omics of plants in response to stress conditions play more crucial roles in the post-genomic era. High-quality genomic data provide more deeper understanding of how plants to survive under environmental stresses. This book is focused on concluding the recent progress in the Protein and Proteome Atlas in plants under different stresses. It covers various aspects of plant protein ranging from agricultural proteomics, structure and function of proteins, and approaches for protein identification and quantification.

Keywords

proteomic --- postharvest freshness --- ATP synthase --- ATP synthase CF1 alpha subunit (chloroplast) --- chlorophyll fluorescence parameters --- photosynthetic parameters --- drought stress --- Triticum aestivum L. --- comparative proteomic analysis --- iTRAQ --- VIGS --- Jatropha curcas --- phosphoproteomics --- seedling --- chilling stress --- regulated mechanism --- Alternanthera philoxeroides --- proteomic --- stem --- potassium --- stress --- Salinity stress --- Dunaliella salina --- isobaric tags for relative and absolute quantitation --- differentially abundant proteins --- proteomics --- arbuscular mycorrhizal fungi --- salt stress --- E. angustifolia --- proteomics --- wheat --- root --- wood vinegar --- drought stress --- ROS --- ABA --- proteome --- maize --- AGPase --- phosphorylation --- brittle-2 --- phos-tagTM --- MIPS --- exon-intron structure diversity --- Gossypium hirsutum --- loss-of-function mutant --- root cell elongation --- CHA-SQ-1 --- cytomorphology --- pollen abortion --- proteomics --- wheat --- cotton --- somatic embryogenesis --- transdifferentiation --- quantitative proteomics --- regulation and metabolism --- molecular basis --- concerted network --- maize --- phosphoproteomics --- salt tolerance --- label-free quantification --- root and shoot --- sugar beet --- salt stress --- S-adenosylmethionine decarboxylase --- ROS --- antioxidant enzyme --- cotton --- somatic embryogenesis --- transdifferentiation --- widely targeted metabolomics --- purine metabolism --- flavonoid biosynthesis --- molecular and biochemical basis --- transcript-metabolite network --- leaf sheath --- maturation --- transcriptional dynamics --- transcriptome --- abiotic stress --- silicate limitation --- diatom --- iTRAQ --- proteomics --- photosynthesis --- carbon fixation --- natural rubber biosynthesis --- mass spectrometry --- rubber grass --- rubber latex --- shotgun proteomics --- Taraxacum kok-saghyz --- two-dimensional gel electrophoresis --- visual proteome map --- proteomics --- wheat --- drought --- leaf --- iTRAQ --- micro-exons --- constitutive splicing --- alternative splicing --- ancient genes --- domain --- radish --- heat stress --- transcriptome sequencing --- lncRNA --- miRNA --- physiological response --- Millettia pinnata --- woody oilseed plants --- seed development --- miRNA --- nitrogen fertilizer --- rice --- proteome --- cultivars --- nitrogen use efficiency (NUE) --- Nelumbo nucifera --- phylogeny --- genomics --- molecular mechanisms --- model plant --- proteomes --- iTRAQ --- filling kernel --- drought stress --- heat shock proteins --- Zea mays L. --- wucai --- low-temperature stress --- high-temperature stress --- proteomics --- redox homeostasis --- GLU1 --- glutathione --- heat response --- heat-sensitive spinach variety --- proteomics --- ROS scavenging --- inositol --- phosphatidylinositol --- phosphatase --- stress --- signaling pathway --- integrated omics --- plants under stress --- post-genomics era --- proteome atlas --- quantitative proteomics

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