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Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889451975 Year: Pages: 102 DOI: 10.3389/978-2-88945-197-5 Language: English
Publisher: Frontiers Media SA
Subject: Environmental Sciences --- Science (General)
Added to DOAB on : 2017-10-13 14:57:01
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Abstract

Tens of thousands of chemicals are released into the environment every day. High-throughput screening (HTS) has offered a more efficient and cost-effective alternative to traditional toxicity tests that can profile these chemicals for potential adverse effects with the aim to prioritize a manageable number for more in depth testing and to provide clues to mechanism of toxicity. The Tox21 program, a collaboration between the National Institute of Environmental Health Sciences (NIEHS)/National Toxicology Program (NTP), the U.S. Environmental Protection Agency’s (EPA) National Center for Computational Toxicology (NCCT), the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS), and the U.S. Food and Drug Administration (FDA), has generated quantitative high-throughput screening (qHTS) data on a library of 10K compounds, including environmental chemicals and drugs, against a panel of nuclear receptor and stress response pathway assays during its production phase (phase II). The Tox21 Challenge, a worldwide modeling competition, was launched that asks a “crowd” of researchers to use these data to elucidate the extent to which the interference of biochemical and cellular pathways by compounds can be inferred from chemical structure data. In the Challenge participants were asked to model twelve assays related to nuclear receptor and stress response pathways using the data generated against the Tox21 10K compound library as the training set. The computational models built within this Challenge are expected to improve the community’s ability to prioritize novel chemicals with respect to potential concern to human health. This research topic presents the resulting computational models with good predictive performance from this Challenge.

Earth Observation, Remote Sensing and Geoscientific Ground Investigations for Archaeological and Heritage Research

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ISBN: 9783039211937 / 9783039211944 Year: Pages: 304 DOI: 10.3390/books978-3-03921-194-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-08-28 11:21:27
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This book collects 15 papers written by renowned scholars from across the globe that showcase the forefront research in Earth observation (EO), remote sensing (RS), and geoscientific ground investigations to study archaeological records and cultural heritage.Archaeologists, anthropologists, geographers, remote sensing, and archaeometry experts share their methodologies relying on a wealth of techniques and data including, but not limited to: very high resolution satellite images from optical and radar space-borne sensors, air-borne surveys, geographic information systems (GIS), archaeological fieldwork, and historical maps.A couple of the contributions highlight the value of noninvasive and nondestructive laboratory analyses (e.g., neutron diffraction) to reconstruct ancient manufacturing technologies, and of geological ground investigations to corroborate hypotheses of historical events that shaped cultural landscapes.Case studies encompass famous UNESCO World Heritage Sites (e.g., the Nasca Lines in Peru), remote and yet-to-discover archaeological areas in tropical forests in central America, European countries, south Asian changing landscapes, and environments which are arid nowadays but were probably full of woody vegetation in the past.Finally, the reader can learn about the state-of-the-art of education initiatives to train site managers in the use of space technologies in support of their activities, and can understand the legal aspects involved in the application of EO and RS to address current challenges of African heritage preservation.

Keywords

analytic hierarchy process (AHP) --- archaeology --- predictive model --- tumuli --- remote sensing --- multi-criteria --- Saharan Morocco --- airborne laser scanning --- orthophotographs --- archaeological survey --- field reconnaissance --- Arran --- national archaeological mapping programme --- synthetic aperture radar --- subsurface imaging --- microwave penetration --- archaeology --- arid environments --- remote sensing --- Oman --- e-learning --- Earth observation --- education --- capacity development --- cultural and natural heritage --- UNESCO --- photogrammetry --- RPAS --- UAV --- Peru --- geoglyph Pista --- mapping --- drones --- remote sensing --- free satellite imagery --- GoogleEarth --- Bing Maps --- archaeological fieldwork --- arid environments --- basalt desert --- landscape accessibility --- Harra --- Jordan --- archaeological landscapes --- settlements --- historical maps --- Survey of India --- Archaeological Survey of India --- heritage --- colonial studies --- remote sensing --- historical landscapes --- landscape archaeology --- settlements --- colonial studies --- river morphology --- Indus --- floods --- remote sensing --- satellite --- Sentinel-2 --- surface survey --- Roman archaeology --- Sumerian pottery --- neutron techniques --- neutron diffraction --- chemometric analysis --- Mega El Niño --- pampa of Nazca --- Cuenca Pisco --- Rio Grande de Nazca --- grain-size --- volcaniclastic layer --- stratigraphy --- petrography --- Lidar --- GIS --- Mesoamerica --- Archaeology --- Caves --- Landscape --- Ritual --- Visualization --- Maya --- Belize --- Sacred --- automated detection --- OBIA --- LiDAR --- Difference Map --- field monument --- Burial Mound --- Motte-and-Bailey castle --- Ridge and Furrow --- space law --- disaster and conservation management --- Geographic Information System (GIS) --- international boundaries --- Africa --- Cameroon-Nigeria Mixed Commission --- satellite imagery --- Boundary Demarcation --- international law --- relict boundaries --- Earth Observation --- remote sensing --- optical --- SAR --- drone --- airborne LiDAR --- GIS --- OBIA --- neutron diffraction --- archaeological prospection --- pattern recognition --- archaeometry --- geological mapping

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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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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