| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910557545803321 |
|
|
Autore |
Jiang Hui |
|
|
Titolo |
Statistical Methods for the Analysis of Genomic Data |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
|
|
|
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (136 p.) |
|
|
|
|
|
|
Soggetti |
|
Mathematics and Science |
Research and information: general |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Sommario/riassunto |
|
In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement. |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910404092303321 |
|
|
Autore |
Moreno Antônio |
|
|
Titolo |
Sentiment Analysis for Social Media |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (152 p.) |
|
|
|
|
|
|
Soggetti |
|
History of engineering and technology |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Sommario/riassunto |
|
Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection. |
|
|
|
|
|
|
|
| |