noncode is an integrated knowledge database dedicated to non-coding RNAs (ncRNAs), that is to say, RNAs that function without being translated into proteins. All ncRNAs in noncode were filtered automatically from lite...
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noncode is an integrated knowledge database dedicated to non-coding RNAs (ncRNAs), that is to say, RNAs that function without being translated into proteins. All ncRNAs in noncode were filtered automatically from literature and GenBank, and were later manually curated. The distinctive features of noncode are as follows: (i) the ncRNAs in noncode include almost all the types of ncRNAs, except transfer RNAs and ribosomal RNAs. (ii) All ncRNA sequences and their related information (e.g. function, cellular role, cellular location, chromosomal information, etc.) in noncode have been confirmed manually by consulting relevant literature: more than 80% of the entries are based on experimental data. (iii) Based on the cellular process and function, which a given ncRNA is involved in,we introduced a novel classification system, labeled process function class, to integrate existing classification systems. (iv) In addition, some 1100 ncRNAs have been grouped into nine other classes according to whether they are specific to gender or tissue or associated with tumors and diseases, etc. (v) noncode provides a user-friendly interface, a visualization platform and a convenient search option, allowing efficient recovery of sequence, regulatory elements in the flanking sequences, secondary structure, related publications and other information. The first release of noncode (v1.0) contains 5339 non-redundant sequences from 861 organisms, including eukaryotes, eubacteria, archaebacteria, virus and viroids. Access is free for all users through a web interface at http://***.
Aim: To construct a comprehensive pig noncoding transcriptome and further enhance porcine noncoding genome annotation. Materials & methods: We performed a tissue-based long noncoding RNA (lncRNA) profiling via exp...
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Aim: To construct a comprehensive pig noncoding transcriptome and further enhance porcine noncoding genome annotation. Materials & methods: We performed a tissue-based long noncoding RNA (lncRNA) profiling via exploiting 32,212 nonredundant lncRNA isoforms corresponding to 18,676 lncRNA loci across 34 normal pig tissues using high-throughput sequencing. Furthermore, the potential relationship between our identified lncRNAs and known protein-coding genes were globally assessed via a comprehensive computation-based strategy, developing a genome-wide lncRNA-targeted genome draft for further functional studies on noncoding genes. Results & conclusion: Among these lncRNAs, ubiquitously expressed lncRNA appeared at a higher level compared with tissue-specific one. Findings herein provide insight into comprehensive knowledge of porcine noncoding RNAs and further enhance pig noncoding annotation. For ease of accessing the information of the identified lncRNAs, we deposited those with high confidence in the publicly available noncode database, providing a valuable resource for facilitating pig noncoding genomic studies.
Because of non-coding sequences playing more and more important roles in the process of translation, it has very important significance to research non-coding region and its function. In the recent years, the research...
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ISBN:
(纸本)9780769535562
Because of non-coding sequences playing more and more important roles in the process of translation, it has very important significance to research non-coding region and its function. In the recent years, the researches have been made great progress on the non-coding regions, especially about nonprotein-coding RNA (ncRNAs). The Z curve is a very useful method for visualizing and analyzing DNA sequences. It is a three-dimensional space curve constituting the unique representation of a given DNA sequence in the sense that each can be uniquely reconstructed from the other. Based on the Z curve, this paper picks up 20 Specific ncRNAs (BC200 RNA and BC1 RNA) sequences from the noncode database, which relate with disease-cancer and come from different organisms. The corresponding Z curves of the ncRNAs sequences have been mapped and compared. The geometrical features of the studied ncRNA sequences are obtained. These features indicate the ncRNA sequences having same functions have almost same Z-curve shapes or tendency and base content in spite of difference of organisms.
It has become very important to study non-coding RNAs in the recent years. The Z curve is a very useful method for visualizing and analyzing DNA sequences among the approaches of researching ncRNAs. It is a three-dime...
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It has become very important to study non-coding RNAs in the recent years. The Z curve is a very useful method for visualizing and analyzing DNA sequences among the approaches of researching ncRNAs. It is a three-dimensional space curve that constitutes a unique representation of a given DNA sequence, i.e., both the Z-curver and the given DNA sequence can be uniquely reconstructed from the other. Using Z curve method, we select 15 disease related ncRNAs sequences from the noncode database, which relate with Alzheimer Disease. The corresponding Z curves of the studied ncRNAs, sequences have been mapped and compared. The statistical features of the Z curves are obtained. These features indicate that the ncRNAs sequences, which play same roles in the celluar process, have almost the same Z-curves. And the base content in these sequences is almost same too, in spite of coming from different organisms.
We present an introduction to RNA databases. The history and technology behind RNA databases are briefly discussed. We examine differing methods of data collection and curation and discuss their impact on both the sco...
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We present an introduction to RNA databases. The history and technology behind RNA databases are briefly discussed. We examine differing methods of data collection and curation and discuss their impact on both the scope and accuracy of the resulting databases. Finally, we demonstrate these principles through detailed examination of four leading RNA databases: noncode, miRBase, Rfam, and SILVA.
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