Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
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 |
Wan Shibiao
|
||
| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Clastic Hydrocarbon Reservoir Sedimentology [[electronic resource] /] / by Xinghe Yu, Shengli Li, Shunli Li
| Clastic Hydrocarbon Reservoir Sedimentology [[electronic resource] /] / by Xinghe Yu, Shengli Li, Shunli Li |
| Autore | Yu Xinghe |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource ( pages) |
| Disciplina | 552.5 |
| Collana | Advances in Oil and Gas Exploration & Production |
| Soggetto topico |
Sedimentology
Fossil fuels Geomorphology Geotechnical engineering Fossil Fuels (incl. Carbon Capture) Geotechnical Engineering & Applied Earth Sciences |
| ISBN | 3-319-70335-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- 1. Formation, Development, and Trends in Reservoir Sedimentology -- Features of Clastic Reservoirs -- Theory and Methods for Studying Clastic Sequence Stratigraphy -- Research Methods of Sedimentary Facies and Sedimentation -- Reservoir Diagenesis -- Reservoir Heterogeneity -- Alluvial Fan Depositional System -- Fluvial Depositional System -- Lacustrine Depositional System -- Deltaic Depositional System -- Sandy Coast (Shore) and Neritic Depositional System -- Deep-water Depositional System -- References -- Index -- Glossary. . |
| Record Nr. | UNINA-9910299371703321 |
|
Yu Xinghe
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||