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Author: Yun Zheng Publisher: Academic Press ISBN: 0128143665 Category : Science Languages : en Pages : 322
Book Description
Computational Non-coding RNA Biology is a resource for the computation of non-coding RNAs. The book covers computational methods for the identification and quantification of non-coding RNAs, including miRNAs, tasiRNAs, phasiRNAs, lariat originated circRNAs and back-spliced circRNAs, the identification of miRNA/siRNA targets, and the identification of mutations and editing sites in miRNAs. The book introduces basic ideas of computational methods, along with their detailed computational steps, a critical component in the development of high throughput sequencing technologies for identifying different classes of non-coding RNAs and predicting the possible functions of these molecules. Finding, quantifying, and visualizing non-coding RNAs from high throughput sequencing datasets at high volume is complex. Therefore, it is usually possible for biologists to complete all of the necessary steps for analysis. - Presents a comprehensive resource of computational methods for the identification and quantification of non-coding RNAs - Introduces 23 practical computational pipelines for various topics of non-coding RNAs - Provides a guide to assist biologists and other researchers dealing with complex datasets - Introduces basic computational methods and provides guidelines for their replication by researchers - Offers a solution to researchers approaching large and complex sequencing datasets
Author: Yun Zheng Publisher: Academic Press ISBN: 0128143665 Category : Science Languages : en Pages : 322
Book Description
Computational Non-coding RNA Biology is a resource for the computation of non-coding RNAs. The book covers computational methods for the identification and quantification of non-coding RNAs, including miRNAs, tasiRNAs, phasiRNAs, lariat originated circRNAs and back-spliced circRNAs, the identification of miRNA/siRNA targets, and the identification of mutations and editing sites in miRNAs. The book introduces basic ideas of computational methods, along with their detailed computational steps, a critical component in the development of high throughput sequencing technologies for identifying different classes of non-coding RNAs and predicting the possible functions of these molecules. Finding, quantifying, and visualizing non-coding RNAs from high throughput sequencing datasets at high volume is complex. Therefore, it is usually possible for biologists to complete all of the necessary steps for analysis. - Presents a comprehensive resource of computational methods for the identification and quantification of non-coding RNAs - Introduces 23 practical computational pipelines for various topics of non-coding RNAs - Provides a guide to assist biologists and other researchers dealing with complex datasets - Introduces basic computational methods and provides guidelines for their replication by researchers - Offers a solution to researchers approaching large and complex sequencing datasets
Author: M.R.S. Rao Publisher: Springer ISBN: 9811052034 Category : Medical Languages : en Pages : 336
Book Description
This contributed volume offers a comprehensive and detailed overview of the various aspects of long non-coding RNAs and discusses their emerging significance. Written by leading experts in the field, it motivates young researchers around the globe, and offers graduate and postgraduate students fascinating insights into genes and their regulation in eukaryotes and higher organisms.
Author: Jan Barciszewski Publisher: Springer Science & Business Media ISBN: 9780306478352 Category : Science Languages : en Pages : 302
Book Description
General inspection of a role performed in the cell by RNAs allows us to distinguish three major groups of transcripts: I. protein-coding mRNAs, II. non-coding housekeeping and III. regulatory RNAs. The housekeeping RNAs include RNA classes that are generally, constitutively expressed and whose presence is required for normal function and viability of the cells. On the other hand, a group of regulatory RNAs includes RNA species that are expressed at certain stages of organism development or cell differentiation or as a response to external stimuli and can affect expression of other genes on the levels of transcription or translation. Non-coding RNA transcripts form a heterogeneous class of RNAs that can not be characterized by a single specific function. Initially, the term non-coding RNA (ncRNA) was used primarily to describe polyadenylated and a capped eukaryotic RNAs transcribed by RNA polymerase II, but lacking long open reading frames. Now, this definition can be extended to cover all RNA transcripts that do not show protein-coding capacity and is sometimes used to describe any RNA that does not encode protein, including introns. This book is an in-depth look at the function of Non-Coding RNAs and their relationship to Molecular Biology and Molecular Biology.
Author: Santosh Kumar Upadhyay Publisher: Academic Press ISBN: 0128214635 Category : Science Languages : en Pages : 392
Book Description
The growth of human population has increased the demand for improved yield and quality of crops and horticultural plants. However, plant productivity continues to be threatened by stresses such as heat, cold, drought, heavy metals, UV radiations, bacterial and fungal pathogens, and insect pests. Long noncoding RNAs are associated with various developmental pathways, regulatory systems, abiotic and biotic stress responses and signaling, and can provide an alternative strategy for stress management in plants. Long Noncoding RNAs in Plants: Roles in development and stress provides the most recent advances in LncRNAs, including identification, characterization, and their potential applications and uses. Introductory chapters include the basic features and brief history of development of lncRNAs studies in plants. The book then provides the knowledge about the lncRNAs in various important agricultural and horticultural crops such as cereals, legumes, fruits, vegetables, and fiber crop cotton, and their roles and applications in abiotic and biotic stress management. - Includes the latest advances and research in long noncoding RNAs in plants - Provides alternative strategies for abiotic and biotic stress management in horticultural plants and agricultural crops - Focuses on the application and uses of long noncoding RNAs
Author: Mathieu Rederstorff Publisher: Humana ISBN: 9781493949038 Category : Medical Languages : en Pages : 0
Book Description
This volume contains state-of-the-art methods tackling all aspects of small non-coding RNAs biology. Small Non-Coding RNAs: Methods and Protocols guides readers through customized dedicated protocols and technologies that will be of valuable help to all those willing to contribute deciphering the numerous functions of small non-coding RNAs. Written in the highly successful Methods of Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols and key tips on troubles troubleshooting and avoiding known pitfalls. Instructive and practical, Small Non-Coding RNAs: Methods and Protocols reaches out to biochemists, cellular and molecular biologists already working in the field of RNA biology and to those just starting to study small non-coding RNAs.
Author: Ka-Chun Wong Publisher: CRC Press ISBN: 1498725007 Category : Science Languages : en Pages : 439
Book Description
The advances in biotechnology such as the next generation sequencing technologies are occurring at breathtaking speed. Advances and breakthroughs give competitive advantages to those who are prepared. However, the driving force behind the positive competition is not only limited to the technological advancement, but also to the companion data analy
Author: Carlos E. Ferreira Publisher: Springer ISBN: 3642150608 Category : Science Languages : en Pages : 88
Book Description
This book constitutes the proceedings of the 5th Brazilian Symposium on Bioinformatics, BSB 2010, held in Rio de Janeiro, Brazil, in August/September 2010. The 5 full papers and 5 extended abstracts presented were carefully reviewed and selected for inclusion in the book. The topics of interest vary in many areas of Bioinformatics, including sequence analysis, motifs, and pattern matching; biomedical text mining; biological databases, data management, integration; biological data mining; structural, comparative, and functional genomics; protein structure, modeling and simulation; gene identification, and regulation; gene expression analysis; gene and protein interaction and networks; molecular docking; molecular evolution and phylogenetics; computational systems biology; computational proteomics; statistical analysis of molecular sequences; algorithms for problems in computational biology; as well as applications in molecular biology, biochemistry, genetics, and associated subjects.
Author: Altuna Akalin Publisher: CRC Press ISBN: 1498781861 Category : Mathematics Languages : en Pages : 463
Book Description
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Author: Yun Zheng
Author: Yun Zheng
Author: M.R.S. Rao
Author: Xin Lai
Author: Jan Barciszewski
Author: Santosh Kumar Upadhyay
Author: Mathieu Rederstorff
Author: Ka-Chun Wong
Author: Bernhard Schölkopf
Author: Carlos E. Ferreira
Author: Altuna Akalin