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Application of Bioinformatics in Cancers
| Application of Bioinformatics in Cancers |
| Autore | Brenner J. Chad |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 online resource (418 p.) |
| Soggetto topico | Biotechnology |
| Soggetto non controllato |
activation induced deaminase
AID/APOBEC alternative splicing anti-cancer artificial intelligence bioinformatics Bioinformatics tool biomarker discovery biomarker signature biomarkers biostatistics brain brain metastases breast cancer breast cancer detection breast cancer prognosis Bufadienolide-like chemicals cancer cancer biomarker cancer biomarkers cancer CRISPR cancer modeling cancer prognosis cancer treatment cancer-related pathways cell-free DNA chemotherapy circulating tumor DNA (ctDNA) classification clinical/environmental factors colorectal cancer comorbidity score Computational Immunology concatenated deep feature copy number aberration copy number variation curation curative surgery datasets decision support systems deep learning denoising autoencoders differential gene expression analysis diseases genes DNA DNA sequence profile drug resistance epigenetics erlotinib estrogen extreme learning false discovery rate feature extraction and interpretation feature selection firehose functional analysis gefitinib gene expression analysis gene inactivation biomarkers gene loss biomarkers gene signature extraction genomic instability GEO DataSets head and neck cancer health strengthening herb hierarchical clustering analysis high-throughput analysis histopathological imaging histopathological imaging features HNSCC hormone sensitive cancers HP hTERT imaging independent prognostic power interaction intratumor heterogeneity knockoffs KRAS mutation locoregionally advanced machine learning meta-analysis methylation microarray miRNA miRNAs mitochondrial metabolism mixture of normal distributions molecular mechanism molecular subtypes Monte Carlo mortality multiple-biomarkers mutable motif mutation Neoantigen Prediction network analysis Network Analysis network pharmacology network target neurological disorders next generation sequencing observed survival interval omics omics profiles oral cancer ovarian cancer overall survival pancreatic cancer pathophysiology PD-L1 precision medicine predictive model protein R package RNA self-organizing map single-biomarkers single-cell sequencing skin cutaneous melanoma somatic mutation StAR steroidogenic enzymes survival analysis TCGA TCGA mining telomerase telomeres The Cancer Genome Atlas traditional Chinese medicine transcriptional signatures treatment de-escalation tumor tumor infiltrating lymphocytes tumor microenvironment variable selection |
| ISBN | 3-03921-789-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367743403321 |
Brenner J. Chad
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass
| Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass |
| Autore | Aranha José |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (276 p.) |
| Soggetto topico |
Geography
Research and information: general |
| Soggetto non controllato |
above-ground biomass
aboveground biomass AGB estimation and mapping allometric equation ALOS DSM ALOS-2 L band SAR bark roughness bioenergy biomass density biomass estimation DBH diameter at breast height ecosystem services forest AGC estimation forest biomass estimation forest growing stock volume forest inventory data forest succession forest type GEOMON GIS individual tree detection landsat Landsat 8 OLI Landsat dataset leaf area index LiDAR machine learning machine learning algorithms mangroves map quality multiple ES interactions multisource remote sensing nondestructive method norway spruce ordinary kriging Pinus massoniana plantations plant area index random forest remote sensing seasonal images sentinel 2 Sentinel-1 C band SAR Sentinel-2 MSI Sentinel-2A shrubs biomass spatiotemporal evolution SPOT6 imagery stand volume stepwise regression subtropical forest subtropical forests support vector machine for regression synergy terrestrial laser scanning trade-off tree height UAV LiDAR urban vegetation valley basin variable selection vegetation indices WorldView-2 Xuzhou |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557474803321 |
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Aranha José
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bioinformatics and Machine Learning for Cancer Biology
| Bioinformatics and Machine Learning for Cancer Biology |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Basel, : MDPI Books, 2022 |
| Descrizione fisica | 1 electronic resource (196 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences |
| Soggetto non controllato |
tumor mutational burden
DNA damage repair genes immunotherapy biomarker biomedical informatics breast cancer estrogen receptor alpha persistent organic pollutants drug-drug interaction networks molecular docking NGS ctDNA VAF liquid biopsy filtering variant calling DEGs diagnosis ovarian cancer PUS7 RMGs CPA4 bladder urothelial carcinoma immune cells T cell exhaustion checkpoint architectural distortion image processing depth-wise convolutional neural network mammography bladder cancer Annexin family survival analysis prognostic signature therapeutic target R Shiny application RNA-seq proteomics multi-omics analysis T-cell acute lymphoblastic leukemia CCLE sitagliptin thyroid cancer (THCA) papillary thyroid cancer (PTCa) thyroidectomy metastasis drug resistance biomarker identification transcriptomics machine learning prediction variable selection major histocompatibility complex bidirectional long short-term memory neural network deep learning cancer incidence mortality modeling forecasting Google Trends Romania ARIMA TBATS NNAR |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595077403321 |
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Wan Shibiao
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| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Soft Sensors
| Intelligent Soft Sensors |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Descrizione fisica | 1 online resource (230 p.) |
| Soggetto topico |
History of engineering and technology
Technology: general issues |
| Soggetto non controllato |
affective computing
bioprocess monitoring BIS index computerized adaptive testing (CAT) D-S evidence theory depth of hypnosis early fire warning EDA electrical resistance executive functions extended Kalman filter extreme learning machine frequency analysis general anesthesia hybrid feature fusion image feature extraction improved mathematical model improved particle swarm algorithm intelligent building system joule heating effect keyframe extraction kinetic model least squares support vector machine modelling multi-source data fusion n/a neurodevelopmental disorders non-linear models nonlinear regression model nonlinear systems observability outliers physiological signals Pichia pastoris population-data-based model prognostic and health management propofol Raman residual model robust observer self-sensing actuation sensor selection shape memory coil simulator sintering quality prediction soft sensor soft sensors soft-sensor based diagnosis spectroscopy state estimation stress detection support vector machine regression model target-controlled infusion total intravenous anesthesia transfer learning variable selection variable stiffness actuation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743269003321 |
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning in Sensors and Imaging
| Machine Learning in Sensors and Imaging |
| Autore | Nam Hyoungsik |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (302 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
activity recognition
artificial neural network BLDC BP artificial neural network burr formation capacitive chaotic system color prior model compressive sensing computer vision coniferous plantations convex optimization convolutional neural network cut interruption deep learning display electric machine protection explainable artificial intelligence extrinsic camera calibration fiber laser forest growing stem volume fuzzy image classification image denoising image encryption imbalanced activities intelligent vehicles laser cutting machine learning machine learning-based classification marine maximum likelihood estimation mixed Poisson-Gaussian likelihood modulation transfer function Naïve bayes neural network noisy non-uniform foundation object detection obstacle avoidance on-shelf availability path planning piston error detection plaintext related plankton Q-learning quality monitoring random forest real-world red-edge band reinforcement learning risk assessment robot arm sampling methods segmented telescope semi-supervised semi-supervised learning SNR star image stochastic analysis structure from motion stylus target reaching temperature estimation texture feature touchscreen transmission-line corridors variable selection vehicle-pavement-foundation interaction wearable sensors wildfire YOLO algorithm |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566484703321 |
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Nam Hyoungsik
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing / Hyung-Sup Jung, Saro Lee
| Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing / Hyung-Sup Jung, Saro Lee |
| Autore | Jung Hyung-Sup |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (438 p.) |
| Soggetto topico | Pharmaceutical chemistry and technology |
| Soggetto non controllato |
artificial neural network
model switching sensitivity analysis neural networks logit boost Qaidam Basin land subsidence land use/land cover (LULC) naïve Bayes multilayer perceptron convolutional neural networks single-class data descriptors logistic regression feature selection mapping particulate matter 10 (PM10) Bayes net gray-level co-occurrence matrix multi-scale Logistic Model Trees classification Panax notoginseng large scene coarse particle grayscale aerial image Gaofen-2 environmental variables variable selection spatial predictive models weights of evidence landslide prediction random forest boosted regression tree convolutional network Vietnam model validation colorization data mining techniques spatial predictions SCAI unmanned aerial vehicle high-resolution texture spatial sparse recovery landslide susceptibility map machine learning reproducible research constrained spatial smoothing support vector machine random forest regression model assessment information gain ALS point cloud bagging ensemble one-class classifiers leaf area index (LAI) landslide susceptibility landsat image ionospheric delay constraints spatial spline regression remote sensing image segmentation panchromatic Sentinel-2 remote sensing optical remote sensing materia medica resource GIS precise weighting change detection TRMM traffic CO crop training sample size convergence time object detection gully erosion deep learning classification-based learning transfer learning landslide traffic CO prediction hybrid model winter wheat spatial distribution logistic alternating direction method of multipliers hybrid structure convolutional neural networks geoherb predictive accuracy real-time precise point positioning spectral bands |
| ISBN |
9783039212163
3039212168 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367564103321 |
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Jung Hyung-Sup
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Metabolomics Data Processing and Data Analysis-Current Best Practices
| Metabolomics Data Processing and Data Analysis-Current Best Practices |
| Autore | Hanhineva Kati |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (276 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
all ion fragmentation
biostatistics bootstrapped-VIP chemical classification combinatorial fragmentation compound identification computational metabolomics computational statistical constraint-based modeling data processing data repository data-dependent acquisition (DDA) data-independent acquisition disease risk enrichment analysis environmental factors experimental design flux balance forensics fragmentation (MS/MS) full-scan MS/MS processing genome-scale metabolic modeling global metabolomics gut microbiome host-microbiome in silico in silico workflows ion selection algorithms LC-MS lipidomics liquid chromatography liquid chromatography high-resolution mass spectrometry liquid chromatography mass spectrometry liquid chromatography-mass spectrometry (LC-MS) liquid chromatography-mass spectrometry (LC/MS) mass spectral libraries mass spectrometry mass spectrometry imaging meta-omics metabolic networks metabolic pathway and network analysis metabolic profiling metabolic reconstructions metabolism metabolite annotation metabolite identification metabolome mining metabolomics metabolomics data mapping metabolomics imaging metagenomics molecular families MS spectral prediction multivariate risk modeling networking nontarget analysis NPLS pathway analysis PLS R programming R-MetaboList 2 reanalysis rule-based fragmentation sample preparation simulator spectra processing structure-based chemical classification substructures supervised learning tandem mass spectral library targeted analysis time series triplot univariate and multivariate statistics unsupervised learning untargeted analysis untargeted metabolomics variable selection wastewater |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557354403321 |
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Hanhineva Kati
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Numerical Linear Algebra and the Applications
| Numerical Linear Algebra and the Applications |
| Autore | Jbilou Khalide |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (126 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
approximation algorithm
chiral media cosine product eigenvalues estimates fixed-point principle Golub-Kahan algorithm high-dimensional inverse scattering Krylov subspaces lanczos method large-scale matrices ℓp-ℓq Lyapunov majorants matrix polynomial minimum norm solution mixed boundary conditions networks non-linear matrix equations nonsymmetric differential matrix Riccati equation PCA Perron root perron vector perturbation perturbation bounds power method pseudospectra quadratic form reciprocity gap functional regularisation SVD tensors Tikhonov upper bounds variable selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557359403321 |
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Jbilou Khalide
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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