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Today, a single laboratory can generate a vast amount of biological data. There is a wealth of data already available in public databases, which makes the modern life sciences almost dependent on bioinformatics. This book brings together an international team of experts to discuss the state-of-the-art from several fields of bioinformatics, from the automatic identification and classification of viruses to the analysis of the transcriptome of single cells and plants, including artificial intelligence algorithms to discover biomarkers and text mining approaches to help in the interpretation of the findings. Machine learning, pattern discovery and analysis, error correction, Bayesian inference and novel computational techniques to discover chromosomal rearrangements continue to play crucial roles in biological discovery, and all of them are explored in chapters of this book. In sum, this book contains high-quality chapters that provide excellent views into key topics of current bioinformatics research, topics that should remain important for the next several years.
Bioinformatics. --- Text Mining Gene Selection; Biological Big Data; Single-Cell RNA Sequencing; Large-Scale Structural Rearrangements in Chromosomes; Machine Learning Approaches; Biomarker Discovery; Gene Expression Data; Bayesian Inference of Gene Expression; Error-Correction Methodologies; Genome Sequencing Data; Plant Transcriptome Assembly; Aligned Pattern Clustering System; Pattern Analysis; Hidden Markov Models; Viral Classification and Discovery; Pattern Discovery and Disentanglement; Aligned Pattern Cluster Analysis; Protein Binding Complexes Detection --- Text Mining Gene Selection; Biological Big Data; Single-Cell RNA Sequencing; Large-Scale Structural Rearrangements in Chromosomes; Machine Learning Approaches; Biomarker Discovery; Gene Expression Data; Bayesian Inference of Gene Expression; Error-Correction Methodologies; Genome Sequencing Data; Plant Transcriptome Assembly; Aligned Pattern Clustering System; Pattern Analysis; Hidden Markov Models; Viral Classification and Discovery; Pattern Discovery and Disentanglement; Aligned Pattern Cluster Analysis; Protein Binding Complexes Detection
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Today, a single laboratory can generate a vast amount of biological data. There is a wealth of data already available in public databases, which makes the modern life sciences almost dependent on bioinformatics. This book brings together an international team of experts to discuss the state-of-the-art from several fields of bioinformatics, from the automatic identification and classification of viruses to the analysis of the transcriptome of single cells and plants, including artificial intelligence algorithms to discover biomarkers and text mining approaches to help in the interpretation of the findings. Machine learning, pattern discovery and analysis, error correction, Bayesian inference and novel computational techniques to discover chromosomal rearrangements continue to play crucial roles in biological discovery, and all of them are explored in chapters of this book. In sum, this book contains high-quality chapters that provide excellent views into key topics of current bioinformatics research, topics that should remain important for the next several years.
Bioinformatics. --- Text Mining Gene Selection; Biological Big Data; Single-Cell RNA Sequencing; Large-Scale Structural Rearrangements in Chromosomes; Machine Learning Approaches; Biomarker Discovery; Gene Expression Data; Bayesian Inference of Gene Expression; Error-Correction Methodologies; Genome Sequencing Data; Plant Transcriptome Assembly; Aligned Pattern Clustering System; Pattern Analysis; Hidden Markov Models; Viral Classification and Discovery; Pattern Discovery and Disentanglement; Aligned Pattern Cluster Analysis; Protein Binding Complexes Detection
Choose an application
Today, a single laboratory can generate a vast amount of biological data. There is a wealth of data already available in public databases, which makes the modern life sciences almost dependent on bioinformatics. This book brings together an international team of experts to discuss the state-of-the-art from several fields of bioinformatics, from the automatic identification and classification of viruses to the analysis of the transcriptome of single cells and plants, including artificial intelligence algorithms to discover biomarkers and text mining approaches to help in the interpretation of the findings. Machine learning, pattern discovery and analysis, error correction, Bayesian inference and novel computational techniques to discover chromosomal rearrangements continue to play crucial roles in biological discovery, and all of them are explored in chapters of this book. In sum, this book contains high-quality chapters that provide excellent views into key topics of current bioinformatics research, topics that should remain important for the next several years.
Bioinformatics. --- Text Mining Gene Selection; Biological Big Data; Single-Cell RNA Sequencing; Large-Scale Structural Rearrangements in Chromosomes; Machine Learning Approaches; Biomarker Discovery; Gene Expression Data; Bayesian Inference of Gene Expression; Error-Correction Methodologies; Genome Sequencing Data; Plant Transcriptome Assembly; Aligned Pattern Clustering System; Pattern Analysis; Hidden Markov Models; Viral Classification and Discovery; Pattern Discovery and Disentanglement; Aligned Pattern Cluster Analysis; Protein Binding Complexes Detection
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Health is defined as “the state of the organism when it functions optimally without evidence of disease”. Surprisingly, the words “microbes” or “microorganism” are missing in this definition. The regulation of gut microbiota is mediated by an enormous quantity of aspects, such as microbiological factors, host characteristics, diet patterns, and environmental variables. Some protective, structural, and metabolic functions have been reported for gut microbiota, and these functions are related to the regulation of homeostasis and host health. Host defense against pathogens is, in part, mediated through gut microbiota action and requires intimate interpretation of the current microenvironment and discrimination between commensal and occasional bacteria. The present Special Issue provides a summary of the progress on the topic of intestinal microbiota and its important role in human health in different populations. This Special Issue will be of great interest from a clinical and public health perspective. Nevertheless, more studies with more samples and comparable methods are necessary to understand the actual function of intestinal microbiota in disease development and health maintenance.
Research & information: general --- Biology, life sciences --- sperm quality --- probiotics --- zebrafish --- motility --- behavior --- intestinal microbiota --- intestinal Bacteroides --- cardiorespiratory fitness --- trunk muscle training --- aerobic exercise training --- brisk walking --- nutrients --- gut microbiota --- nutrition --- habitual diets --- Western diet --- obesity --- cardiometabolic risk factors --- chronic health conditions --- gastrointestinal disorders --- prebiotics and probiotics --- metabolic syndrome --- gastrointestinal microbiome --- Lactobacillus reuteri V3401 --- sugar alcohol --- prebiotic --- bowel function --- immune function --- respiratory tract infections --- otitis media --- sinusitis --- weight management --- satiety --- bone health --- AMP-activated protein kinase --- butyrate --- developmental origins of health and disease (DOHaD) --- high fat diet --- hypertension --- nutrient-sensing signals --- propionate --- short chain fatty acids --- kefir --- autism spectrum disorders --- oral microbiota --- dysbiosis --- co-occurring conditions --- allergy --- abdominal pain --- biomarker discovery --- anorexia --- food restriction --- ClpB --- microbiota --- Enterobacteriaceae --- inulin --- circadian rhythm --- feeding timing --- choline --- trimethylamine --- trimethylamine n-oxide --- 16S rRNA gene profiling --- qPCR --- linear mixed models --- soy protein --- lipid metabolism --- circadian --- chrono-nutrition --- microbiome --- pregnancy --- fetus --- placenta --- newborn --- infancy --- critical illness --- sepsis --- lipid metabolome --- amlodipine --- corticosterone --- ACTH --- gut bacteriome --- ischemia-reperfusion injury --- nutritional status --- supplemented nutrition --- partial hepatectomy --- liver transplantation --- vaginal microbiome --- bacterial communities --- vaginal dysbiosis --- bacterial vaginosis --- risk factors --- hormone replacement therapy --- cardiovascular diseases --- atherosclerosis --- prebiotics --- alanine aminotransferase --- antibiotic --- Optifast --- gut microbiome --- metronidazole --- nonnutritive sweeteners --- sweetening agents --- sperm quality --- probiotics --- zebrafish --- motility --- behavior --- intestinal microbiota --- intestinal Bacteroides --- cardiorespiratory fitness --- trunk muscle training --- aerobic exercise training --- brisk walking --- nutrients --- gut microbiota --- nutrition --- habitual diets --- Western diet --- obesity --- cardiometabolic risk factors --- chronic health conditions --- gastrointestinal disorders --- prebiotics and probiotics --- metabolic syndrome --- gastrointestinal microbiome --- Lactobacillus reuteri V3401 --- sugar alcohol --- prebiotic --- bowel function --- immune function --- respiratory tract infections --- otitis media --- sinusitis --- weight management --- satiety --- bone health --- AMP-activated protein kinase --- butyrate --- developmental origins of health and disease (DOHaD) --- high fat diet --- hypertension --- nutrient-sensing signals --- propionate --- short chain fatty acids --- kefir --- autism spectrum disorders --- oral microbiota --- dysbiosis --- co-occurring conditions --- allergy --- abdominal pain --- biomarker discovery --- anorexia --- food restriction --- ClpB --- microbiota --- Enterobacteriaceae --- inulin --- circadian rhythm --- feeding timing --- choline --- trimethylamine --- trimethylamine n-oxide --- 16S rRNA gene profiling --- qPCR --- linear mixed models --- soy protein --- lipid metabolism --- circadian --- chrono-nutrition --- microbiome --- pregnancy --- fetus --- placenta --- newborn --- infancy --- critical illness --- sepsis --- lipid metabolome --- amlodipine --- corticosterone --- ACTH --- gut bacteriome --- ischemia-reperfusion injury --- nutritional status --- supplemented nutrition --- partial hepatectomy --- liver transplantation --- vaginal microbiome --- bacterial communities --- vaginal dysbiosis --- bacterial vaginosis --- risk factors --- hormone replacement therapy --- cardiovascular diseases --- atherosclerosis --- prebiotics --- alanine aminotransferase --- antibiotic --- Optifast --- gut microbiome --- metronidazole --- nonnutritive sweeteners --- sweetening agents
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The book highlights important aspects of Molecular Psychiatry, including molecular mechanisms, animal models, biomarkers, advanced methods, drugs and antidepressant response, as well as genetics and epigenetics. Molecular mechanisms are a vital part of the search for the biological basis of psychiatric disorders, providing molecular hints that can later be tested as biomarkers or targets for drug development. Animal models represent a commonly used approach to aid in this bench-to-bed translation; the examples here are social defeat stress and the Roman High-Avoidance (RHA) and the Roman Low-Avoidance (RLA) rats. For biomarkers, psychiatric disorders pose a particular challenge due to the tissue specificity of many currently investigated biomarkers; i.e., not all blood-based measures directly represent changes in the brain. The Ebook includes five articles focused on the challenges of identifying clinically and biologically relevant biomarkers for psychiatric disorders. Scientific progress typically is fostered by the development of new methods. The application of machine learning methods for the proper analysis of Big Data and induced pluripotent stem cells are examples outlined in this Ebook. Furthermore, three articles are devoted to the understanding of the mechanisms of actions of existing drugs with the ultimate goal of identifying ways to predict treatment response in patients. Finally, three articles deepen the insight into the genetics and epigenetics of psychiatric disorders.
Medicine --- Mental health services --- cardiovascular disease --- cell adhesion molecules --- immunology --- inflammation --- nervous system --- schizophrenia --- bipolar disorder --- major depressive disorder --- DNA methylation --- response variability --- antipsychotics --- drug design --- multi-target drugs --- polypharmacology --- multi-task learning --- machine learning --- biomarker discovery --- psychiatry --- serotonin --- 5-HT 4 receptor --- 5-HT4R --- depression --- mood disorder --- expression --- Alzheimer's disease --- cognition --- Parkinson's disease --- forced swimming --- Roman rat lines --- stress --- hippocampus --- BDNF --- trkB --- PSA-NCAM --- western blot --- immunohistochemistry --- general cognitive function --- intelligence --- GWAS --- genetic correlation --- childhood-onset schizophrenia (COS) --- induced pluripotent stem cell (iPSC) --- copy number variation (CNV) --- early neurodevelopment --- neuronal differentiation --- synapse --- dendritic arborization --- miRNAs --- stress physiology --- cytoskeleton --- actin dynamics --- DRR1 --- TU3A --- FAM107A --- acid sphingomyelinase --- alcohol dependence --- liver enzymes --- sphingolipid metabolism --- withdrawal --- Hsp90 --- GR --- stress response --- steroid hormones --- molecular chaperones --- psychiatric disease --- circadian rhythms --- FKBP51 --- FKBP52 --- CyP40 --- PP5 --- DISC1 --- neurodevelopment --- CRMP-2 --- proteomics --- antidepressant treatment --- HPA axis --- gene expression --- FKBP5 --- sleep --- sleep EEG --- biomarkers --- antidepressants --- cordance --- gender --- sex difference --- antidepressant --- rapid-acting --- Ketamine --- endocrinology --- (2R,6R)-Hydroxynorketamine --- electroconvulsive therapy --- basic-helix-loop-helix --- brain --- coactivator --- glucocorticoids --- mineralocorticoid receptor knockout --- transcription biology --- dopaminergic gene polymorphisms --- affective temperament --- obesity --- alpha-synuclein --- SNCA --- major depression --- Hamilton Scale of Depression --- chemokines --- neuroinflammation --- social defeat --- Immune response --- T cells --- susceptibility --- resilience --- Treg cells --- Th17 cells --- behavior --- PPARγ --- cardiovascular disease --- cell adhesion molecules --- immunology --- inflammation --- nervous system --- schizophrenia --- bipolar disorder --- major depressive disorder --- DNA methylation --- response variability --- antipsychotics --- drug design --- multi-target drugs --- polypharmacology --- multi-task learning --- machine learning --- biomarker discovery --- psychiatry --- serotonin --- 5-HT 4 receptor --- 5-HT4R --- depression --- mood disorder --- expression --- Alzheimer's disease --- cognition --- Parkinson's disease --- forced swimming --- Roman rat lines --- stress --- hippocampus --- BDNF --- trkB --- PSA-NCAM --- western blot --- immunohistochemistry --- general cognitive function --- intelligence --- GWAS --- genetic correlation --- childhood-onset schizophrenia (COS) --- induced pluripotent stem cell (iPSC) --- copy number variation (CNV) --- early neurodevelopment --- neuronal differentiation --- synapse --- dendritic arborization --- miRNAs --- stress physiology --- cytoskeleton --- actin dynamics --- DRR1 --- TU3A --- FAM107A --- acid sphingomyelinase --- alcohol dependence --- liver enzymes --- sphingolipid metabolism --- withdrawal --- Hsp90 --- GR --- stress response --- steroid hormones --- molecular chaperones --- psychiatric disease --- circadian rhythms --- FKBP51 --- FKBP52 --- CyP40 --- PP5 --- DISC1 --- neurodevelopment --- CRMP-2 --- proteomics --- antidepressant treatment --- HPA axis --- gene expression --- FKBP5 --- sleep --- sleep EEG --- biomarkers --- antidepressants --- cordance --- gender --- sex difference --- antidepressant --- rapid-acting --- Ketamine --- endocrinology --- (2R,6R)-Hydroxynorketamine --- electroconvulsive therapy --- basic-helix-loop-helix --- brain --- coactivator --- glucocorticoids --- mineralocorticoid receptor knockout --- transcription biology --- dopaminergic gene polymorphisms --- affective temperament --- obesity --- alpha-synuclein --- SNCA --- major depression --- Hamilton Scale of Depression --- chemokines --- neuroinflammation --- social defeat --- Immune response --- T cells --- susceptibility --- resilience --- Treg cells --- Th17 cells --- behavior --- PPARγ
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Health is defined as “the state of the organism when it functions optimally without evidence of disease”. Surprisingly, the words “microbes” or “microorganism” are missing in this definition. The regulation of gut microbiota is mediated by an enormous quantity of aspects, such as microbiological factors, host characteristics, diet patterns, and environmental variables. Some protective, structural, and metabolic functions have been reported for gut microbiota, and these functions are related to the regulation of homeostasis and host health. Host defense against pathogens is, in part, mediated through gut microbiota action and requires intimate interpretation of the current microenvironment and discrimination between commensal and occasional bacteria. The present Special Issue provides a summary of the progress on the topic of intestinal microbiota and its important role in human health in different populations. This Special Issue will be of great interest from a clinical and public health perspective. Nevertheless, more studies with more samples and comparable methods are necessary to understand the actual function of intestinal microbiota in disease development and health maintenance.
sperm quality --- probiotics --- zebrafish --- motility --- behavior --- intestinal microbiota --- intestinal Bacteroides --- cardiorespiratory fitness --- trunk muscle training --- aerobic exercise training --- brisk walking --- nutrients --- gut microbiota --- nutrition --- habitual diets --- Western diet --- obesity --- cardiometabolic risk factors --- chronic health conditions --- gastrointestinal disorders --- prebiotics and probiotics --- metabolic syndrome --- gastrointestinal microbiome --- Lactobacillus reuteri V3401 --- sugar alcohol --- prebiotic --- bowel function --- immune function --- respiratory tract infections --- otitis media --- sinusitis --- weight management --- satiety --- bone health --- AMP-activated protein kinase --- butyrate --- developmental origins of health and disease (DOHaD) --- high fat diet --- hypertension --- nutrient-sensing signals --- propionate --- short chain fatty acids --- kefir --- autism spectrum disorders --- oral microbiota --- dysbiosis --- co-occurring conditions --- allergy --- abdominal pain --- biomarker discovery --- anorexia --- food restriction --- ClpB --- microbiota --- Enterobacteriaceae --- inulin --- circadian rhythm --- feeding timing --- choline --- trimethylamine --- trimethylamine n-oxide --- 16S rRNA gene profiling --- qPCR --- linear mixed models --- soy protein --- lipid metabolism --- circadian --- chrono-nutrition --- microbiome --- pregnancy --- fetus --- placenta --- newborn --- infancy --- critical illness --- sepsis --- lipid metabolome --- amlodipine --- corticosterone --- ACTH --- gut bacteriome --- ischemia-reperfusion injury --- nutritional status --- supplemented nutrition --- partial hepatectomy --- liver transplantation --- vaginal microbiome --- bacterial communities --- vaginal dysbiosis --- bacterial vaginosis --- risk factors --- hormone replacement therapy --- cardiovascular diseases --- atherosclerosis --- prebiotics --- alanine aminotransferase --- antibiotic --- Optifast --- gut microbiome --- metronidazole --- nonnutritive sweeteners --- sweetening agents --- n/a
Choose an application
The book highlights important aspects of Molecular Psychiatry, including molecular mechanisms, animal models, biomarkers, advanced methods, drugs and antidepressant response, as well as genetics and epigenetics. Molecular mechanisms are a vital part of the search for the biological basis of psychiatric disorders, providing molecular hints that can later be tested as biomarkers or targets for drug development. Animal models represent a commonly used approach to aid in this bench-to-bed translation; the examples here are social defeat stress and the Roman High-Avoidance (RHA) and the Roman Low-Avoidance (RLA) rats. For biomarkers, psychiatric disorders pose a particular challenge due to the tissue specificity of many currently investigated biomarkers; i.e., not all blood-based measures directly represent changes in the brain. The Ebook includes five articles focused on the challenges of identifying clinically and biologically relevant biomarkers for psychiatric disorders. Scientific progress typically is fostered by the development of new methods. The application of machine learning methods for the proper analysis of Big Data and induced pluripotent stem cells are examples outlined in this Ebook. Furthermore, three articles are devoted to the understanding of the mechanisms of actions of existing drugs with the ultimate goal of identifying ways to predict treatment response in patients. Finally, three articles deepen the insight into the genetics and epigenetics of psychiatric disorders.
cardiovascular disease --- cell adhesion molecules --- immunology --- inflammation --- nervous system --- schizophrenia --- bipolar disorder --- major depressive disorder --- DNA methylation --- response variability --- antipsychotics --- drug design --- multi-target drugs --- polypharmacology --- multi-task learning --- machine learning --- biomarker discovery --- psychiatry --- serotonin --- 5-HT 4 receptor --- 5-HT4R --- depression --- mood disorder --- expression --- Alzheimer’s disease --- cognition --- Parkinson’s disease --- forced swimming --- Roman rat lines --- stress --- hippocampus --- BDNF --- trkB --- PSA-NCAM --- western blot --- immunohistochemistry --- general cognitive function --- intelligence --- GWAS --- genetic correlation --- childhood-onset schizophrenia (COS) --- induced pluripotent stem cell (iPSC) --- copy number variation (CNV) --- early neurodevelopment --- neuronal differentiation --- synapse --- dendritic arborization --- miRNAs --- stress physiology --- cytoskeleton --- actin dynamics --- DRR1 --- TU3A --- FAM107A --- acid sphingomyelinase --- alcohol dependence --- liver enzymes --- sphingolipid metabolism --- withdrawal --- Hsp90 --- GR --- stress response --- steroid hormones --- molecular chaperones --- psychiatric disease --- circadian rhythms --- FKBP51 --- FKBP52 --- CyP40 --- PP5 --- DISC1 --- neurodevelopment --- CRMP-2 --- proteomics --- antidepressant treatment --- HPA axis --- gene expression --- FKBP5 --- sleep --- sleep EEG --- biomarkers --- antidepressants --- cordance --- gender --- sex difference --- antidepressant --- rapid-acting --- Ketamine --- endocrinology --- (2R,6R)-Hydroxynorketamine --- electroconvulsive therapy --- basic-helix-loop-helix --- brain --- coactivator --- glucocorticoids --- mineralocorticoid receptor knockout --- transcription biology --- dopaminergic gene polymorphisms --- affective temperament --- obesity --- alpha-synuclein --- SNCA --- major depression --- Hamilton Scale of Depression --- chemokines --- neuroinflammation --- social defeat --- Immune response --- T cells --- susceptibility --- resilience --- Treg cells --- Th17 cells --- behavior --- PPARγ --- n/a --- Alzheimer's disease --- Parkinson's disease
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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.
cancer treatment --- extreme learning --- independent prognostic power --- AID/APOBEC --- HP --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- artificial intelligence --- epigenetics --- comorbidity score --- denoising autoencoders --- protein --- single-biomarkers --- gene signature extraction --- high-throughput analysis --- concatenated deep feature --- feature selection --- differential gene expression analysis --- colorectal cancer --- ovarian cancer --- multiple-biomarkers --- gefitinib --- cancer biomarkers --- classification --- cancer biomarker --- mutation --- hierarchical clustering analysis --- HNSCC --- cell-free DNA --- network analysis --- drug resistance --- hTERT --- variable selection --- KRAS mutation --- single-cell sequencing --- network target --- skin cutaneous melanoma --- telomeres --- Neoantigen Prediction --- datasets --- clinical/environmental factors --- StAR --- PD-L1 --- miRNA --- circulating tumor DNA (ctDNA) --- false discovery rate --- predictive model --- Computational Immunology --- brain metastases --- observed survival interval --- next generation sequencing --- brain --- machine learning --- cancer prognosis --- copy number aberration --- mutable motif --- steroidogenic enzymes --- tumor --- mortality --- tumor microenvironment --- somatic mutation --- transcriptional signatures --- omics profiles --- mitochondrial metabolism --- Bufadienolide-like chemicals --- cancer-related pathways --- intratumor heterogeneity --- estrogen --- locoregionally advanced --- RNA --- feature extraction and interpretation --- treatment de-escalation --- activation induced deaminase --- knockoffs --- R package --- copy number variation --- gene loss biomarkers --- cancer CRISPR --- overall survival --- histopathological imaging --- self-organizing map --- Network Analysis --- oral cancer --- biostatistics --- firehose --- Bioinformatics tool --- alternative splicing --- biomarkers --- diseases genes --- histopathological imaging features --- imaging --- TCGA --- decision support systems --- The Cancer Genome Atlas --- molecular subtypes --- molecular mechanism --- omics --- curative surgery --- network pharmacology --- methylation --- bioinformatics --- neurological disorders --- precision medicine --- cancer modeling --- miRNAs --- breast cancer detection --- functional analysis --- biomarker signature --- anti-cancer --- hormone sensitive cancers --- deep learning --- DNA sequence profile --- pancreatic cancer --- telomerase --- Monte Carlo --- mixture of normal distributions --- survival analysis --- tumor infiltrating lymphocytes --- curation --- pathophysiology --- GEO DataSets --- head and neck cancer --- gene expression analysis --- erlotinib --- meta-analysis --- traditional Chinese medicine --- breast cancer --- TCGA mining --- breast cancer prognosis --- microarray --- DNA --- interaction --- health strengthening herb --- cancer --- genomic instability
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This book represents one of the most up-to-date collections of articles on clinical practice and research in the field of Autism Spectrum Disorders (ASD). The scholars who contributed to this book are experts in their field, carrying out cutting edge research in prestigious institutes worldwide (e.g., Harvard Medical School, University of California, MIND Institute, King’s College, Karolinska Institute, and many others). The book addressed many topics, including (1) The COVID-19 pandemic; (2) Epidemiology and prevalence; (3) Screening and early behavioral markers; (4) Diagnostic and phenotypic profile; (5) Treatment and intervention; (6) Etiopathogenesis (biomarkers, biology, and genetic, epigenetic, and risk factors); (7) Comorbidity; (8) Adulthood; and (9) Broader Autism Phenotype (BAP). This book testifies to the complexity of performing research in the field of ASD. The published contributions underline areas of progress and ongoing challenges in which more certain data is expected in the coming years. It would be desirable that experts, clinicians, researchers, and trainees could have the opportunity to read this updated text describing the challenging heterogeneity of Autism Spectrum Disorder.
Medicine --- Neurosciences --- autism spectrum disorder --- infants --- frontal EEG alpha asymmetry --- early detection --- autism spectrum disorders --- toddlers --- eye tracking --- joint attention --- longitudinal --- regression --- cytokines --- PAI-1 --- neuroinflammation --- gastrointestinal --- autism --- literature review --- comorbidity --- early intervention --- early intensive behavioral intervention --- behavioral intervention --- First Year Inventory --- early screening --- risk --- cross-cultural generalisability --- validity --- preschool teachers --- self-efficacy --- knowledge --- belief --- skills --- identify --- autism spectrum disorder (ASD) --- level 1 and level 2 screening tools --- systematic review --- COSMIN --- PRISMA --- screening --- infection --- prion --- meta-analysis --- motion analysis --- video signal processing --- neurodevelopmental disorders --- infant screening --- n/a --- developmental language disorder --- semantic features --- word learning --- central coherence --- biomarker --- p-cresol --- mouse social behavior --- dopamine --- ASD --- vision --- proprioception --- self-motion --- immersive virtual reality --- IVR --- HMD --- technology --- persuasive text writing --- perspective-taking --- adolescence --- intervention --- sign language --- imitation --- cognition --- language acquisition --- prevalence estimate --- predictors --- surveillance review --- Autism Spectrum Disorder (ASD) --- early intensive intervention --- developmental trajectories --- moderators and mediators of intervention. --- psychosis --- schizophrenia --- psychopathology --- AQ --- accuracy --- attention to detail --- self-awareness --- insight --- preconception risk factor --- Gilles de la Tourette --- obsession --- compulsion --- social behavior --- social impairment --- sensory profile --- sensory responsiveness --- feeding problems --- short sensory profile (SSP) --- sensory experience questionnaire (SEQ) --- coronavirus --- 2019-nCoV --- neurodevelopment --- child and adolescent psychiatry --- mental health prevention --- Asperger syndrome --- adults --- cerebrospinal fluid --- antibodies --- blood–brain barrier --- GAD65 --- Early Start Denver Model --- high-risk infants --- motor development --- high-functioning autism --- language --- experience --- communication --- autonomic nervous system --- wearable technologies --- EEG --- theory of mind --- adults and adolescents --- human figure drawings --- Draw-a-Man --- drawings maturity --- social perception --- ERP --- reward response --- RewP --- sensitization --- social skills intervention --- PEERS® --- adulthood --- diagnosis --- autistic traits --- action observation --- action prediction --- context --- priors --- hypothalamus --- amygdala --- oxytocin --- social cognition --- social interaction --- affiliative behavior --- neuroimaging --- COVID-19 --- challenging behavior --- dental care --- oral health --- medical procedures --- ICT --- wearable sensors --- migration --- Europe --- health system --- autism in adulthood --- intellectual disability --- regressive autism --- epilepsy --- challenging behaviors --- empathy --- executive functions --- attention deficit and hyperactivity disorder --- disruptive behavior disorders --- alexithymia --- anxiety --- depression --- TAS-20 --- TSIA --- parents --- broader autism phenotype --- autistic-like features --- social-cognitive development --- stereotypical behaviors --- visual impairment --- language profiles --- grammatical comprehension --- cannabinoids --- cannabidiol --- cannabidivarin --- THC --- problem behaviors --- sleep --- hyperactivity --- side effects --- motor performance skills --- Gulf --- BOT-2 --- machine learning --- employment --- telehealth --- ABA --- RCT --- cortisol --- group activity --- stress --- art --- assessment --- sensorimotor integration --- postural balance --- false positive report probability (FPRP) --- Bayesian false-discovery probability (BFDP) --- Genome-Wide Association Studies (GWAS) --- microbiome --- metabolomics --- study design --- biomarker discovery --- precise medicine --- bipolar disorder --- suicidal ideation --- suicidal attempts --- blood-brain barrier
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This book represents one of the most up-to-date collections of articles on clinical practice and research in the field of Autism Spectrum Disorders (ASD). The scholars who contributed to this book are experts in their field, carrying out cutting edge research in prestigious institutes worldwide (e.g., Harvard Medical School, University of California, MIND Institute, King’s College, Karolinska Institute, and many others). The book addressed many topics, including (1) The COVID-19 pandemic; (2) Epidemiology and prevalence; (3) Screening and early behavioral markers; (4) Diagnostic and phenotypic profile; (5) Treatment and intervention; (6) Etiopathogenesis (biomarkers, biology, and genetic, epigenetic, and risk factors); (7) Comorbidity; (8) Adulthood; and (9) Broader Autism Phenotype (BAP). This book testifies to the complexity of performing research in the field of ASD. The published contributions underline areas of progress and ongoing challenges in which more certain data is expected in the coming years. It would be desirable that experts, clinicians, researchers, and trainees could have the opportunity to read this updated text describing the challenging heterogeneity of Autism Spectrum Disorder.
autism spectrum disorder --- infants --- frontal EEG alpha asymmetry --- early detection --- autism spectrum disorders --- toddlers --- eye tracking --- joint attention --- longitudinal --- regression --- cytokines --- PAI-1 --- neuroinflammation --- gastrointestinal --- autism --- literature review --- comorbidity --- early intervention --- early intensive behavioral intervention --- behavioral intervention --- First Year Inventory --- early screening --- risk --- cross-cultural generalisability --- validity --- preschool teachers --- self-efficacy --- knowledge --- belief --- skills --- identify --- autism spectrum disorder (ASD) --- level 1 and level 2 screening tools --- systematic review --- COSMIN --- PRISMA --- screening --- infection --- prion --- meta-analysis --- motion analysis --- video signal processing --- neurodevelopmental disorders --- infant screening --- n/a --- developmental language disorder --- semantic features --- word learning --- central coherence --- biomarker --- p-cresol --- mouse social behavior --- dopamine --- ASD --- vision --- proprioception --- self-motion --- immersive virtual reality --- IVR --- HMD --- technology --- persuasive text writing --- perspective-taking --- adolescence --- intervention --- sign language --- imitation --- cognition --- language acquisition --- prevalence estimate --- predictors --- surveillance review --- Autism Spectrum Disorder (ASD) --- early intensive intervention --- developmental trajectories --- moderators and mediators of intervention. --- psychosis --- schizophrenia --- psychopathology --- AQ --- accuracy --- attention to detail --- self-awareness --- insight --- preconception risk factor --- Gilles de la Tourette --- obsession --- compulsion --- social behavior --- social impairment --- sensory profile --- sensory responsiveness --- feeding problems --- short sensory profile (SSP) --- sensory experience questionnaire (SEQ) --- coronavirus --- 2019-nCoV --- neurodevelopment --- child and adolescent psychiatry --- mental health prevention --- Asperger syndrome --- adults --- cerebrospinal fluid --- antibodies --- blood–brain barrier --- GAD65 --- Early Start Denver Model --- high-risk infants --- motor development --- high-functioning autism --- language --- experience --- communication --- autonomic nervous system --- wearable technologies --- EEG --- theory of mind --- adults and adolescents --- human figure drawings --- Draw-a-Man --- drawings maturity --- social perception --- ERP --- reward response --- RewP --- sensitization --- social skills intervention --- PEERS® --- adulthood --- diagnosis --- autistic traits --- action observation --- action prediction --- context --- priors --- hypothalamus --- amygdala --- oxytocin --- social cognition --- social interaction --- affiliative behavior --- neuroimaging --- COVID-19 --- challenging behavior --- dental care --- oral health --- medical procedures --- ICT --- wearable sensors --- migration --- Europe --- health system --- autism in adulthood --- intellectual disability --- regressive autism --- epilepsy --- challenging behaviors --- empathy --- executive functions --- attention deficit and hyperactivity disorder --- disruptive behavior disorders --- alexithymia --- anxiety --- depression --- TAS-20 --- TSIA --- parents --- broader autism phenotype --- autistic-like features --- social-cognitive development --- stereotypical behaviors --- visual impairment --- language profiles --- grammatical comprehension --- cannabinoids --- cannabidiol --- cannabidivarin --- THC --- problem behaviors --- sleep --- hyperactivity --- side effects --- motor performance skills --- Gulf --- BOT-2 --- machine learning --- employment --- telehealth --- ABA --- RCT --- cortisol --- group activity --- stress --- art --- assessment --- sensorimotor integration --- postural balance --- false positive report probability (FPRP) --- Bayesian false-discovery probability (BFDP) --- Genome-Wide Association Studies (GWAS) --- microbiome --- metabolomics --- study design --- biomarker discovery --- precise medicine --- bipolar disorder --- suicidal ideation --- suicidal attempts --- blood-brain barrier
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