The EMBL data library

Rice, Catherine M.; Fuchs, Rainer; Higgins, Desmond G.; Stoehr, Peter; Cameron, Graham

doi:10.1093/nar/21.13.2967

Cited by 94 publications

(46 citation statements)

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“…Overall, this behaviour is consistent with an unambiguous increase in discriminatory power of the new profile, suggesting that the newly incorporated sequences are dsRBD homologues. Table II records the ranks and scores for searches of SWISS-PROT with individual dsRBD sequences using the fast and sensitive BLITZ server (27). Using a dsRBD sequence from the DAI kinase, which scores highly against the dsRBD profile, Mle-Drome is ranked 9th-above several existing dsRBD entries.…”

Section: Resultsmentioning

confidence: 99%

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Detection of dsRNA-binding domains in RNA helicase A andDrosophilamaleless: implications for monomeric RNA helicases

Gibson

Thompson

1994

Nucl Acids Res

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Section: Resultsmentioning

confidence: 99%

“…Database searches with single sequences These were conducted against SWISS-PROT v. 27 (26) using the EMBL BLITZ network service (27). BLITZ compares sequences using MPsrch (J. Collins and S. Sturrock, Edinburgh) which conducts a full Smith-Waterman (28) local similarity search.…”

Section: Methodsmentioning

confidence: 99%

Detection of dsRNA-binding domains in RNA helicase A andDrosophilamaleless: implications for monomeric RNA helicases

Gibson

Thompson

1994

Nucl Acids Res

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“…the demarcation of domains on the proteins was confirmed by viewing the molecular structure. The corresponding nucleotide sequences are as given in the EMBL database (identifiers given after the slash), comprised of the nucleotide sequence of genes of known primary structure (Rice et al, 1993). The information regarding the subcellular location of the protein was taken from the SWISS-PROT protein sequence data bank (Bairoch & The range of numbered residue portions in the primary structure that form the domain-segments constituting individual domains; they are given by the authors who determined the individual three-dimensional structures (see references in the appropriate PDB files).…”

Section: Rationalementioning

confidence: 99%

“…The nucleotide sequences were extracted from the EMBL nucleotide sequence data bank (Rice et al, 1993) with the aid of the SRS information retrieval computer system (Etzold & Argos, 1993a, 1993b. Only the internal coding regions of the mRNAs (codons 21 through 3 codons prior to the stop codon) were considered because translation-initiation "enhancer" signals occur anywhere in the first 17 codons (McCarthy & Gualerzi, 1994); the minor codons are preferentially located in the 5' coding region (Chen & Inouye, 1990); and the signal for translation-termination extends to two codon positions 5' to the stop codon (Brown et al, 1990).…”

Section: Codon Fractional Frequency Valuesmentioning

confidence: 99%

Ribosome‐mediated translational pause and protein domain organization

1996

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Because regions on the messenger ribonucleic acid differ in the rate at which they are translated by the ribosome and because proteins can fold cotranslationally on the ribosome, a question arises as to whether the kinetics of translation influence the folding events in the growing nascent polypeptide chain. Translationally slow regions were identified on mRNAs for a set of 37 multidomain proteins from Escherichia coli with known three-dimensional structures. The frequencies of individual codons in mRNAs of highly expressed genes from E. coli were taken as a measure of codon translation speed. Analysis of codon usage in slow regions showed a consistency with the experimentally determined translation rates of codons; abundant codons that are translated with faster speeds compared with their synonymous codons were found to be avoided; rare codons that are translated at an unexpectedly higher rate were also found to be avoided in slow regions. The statistical significance of the occurrence of such slow regions on mRNA spans corresponding to the oligopeptide domain termini and linking regions on the encoded proteins was assessed. The amino acid type and the solvent accessibility of the residues coded by such slow regions were also examined. The results indicated that protein domain boundaries that mark higher-order structural organization are largely coded by translationally slow regions on the RNA and are composed of such amino acids that are stickier to the ribosome channel through which the synthesized polypeptide chain emerges into the cytoplasm. The translationally slow nucleotide regions on mRNA possess the potential to form hairpin secondary structures and such structures could further slow the movement of ribosome. The results point to an intriguing correlation between protein synthesis machinery and in vivo protein folding. Examination of available mutagenic data indicated that the effects of some of the reported mutations were consistent with our hypothesis.Keywords: codon usage; domain linkers; peptide channel; protein folding; ribosome; translation The rate of protein translation is nonuniform along the mRNA (Varenne et al., 1984). Ribosomes seem to pause as well as stack at specific regions on mRNA (Chaney & Morris, 1979;Wolin &Walter, 1988;Kim et al., 1991;Kim & Hollingsworth, 1992). Two of the mRNA features that slow the ribosome during translation are the presence of slow codons (Varenne et al., 1984;Bonekamp et al., 1985;Wolin & Walter, 1988) and the formation of higher order nucleotide structures (Chaney & Morris, 1979;Tu et al., 1992). The resultant translational pause may temporally separate the adjacent regions on the growing nascent polypeptide. Given that proteins can fold cotranslationally with the possible involvement of the ribosome (Phillips, 1966;Baldwin, 1975;Yonath, 1992;Kudlicki et al., 1994;Wiedmann et al., 1994;Brimacombe, 1995), the temporal separation might exert a phenotypic effect on the structural organization of the encoded protein. We show that as much as 70% of the do...

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“…Нуклеотидные последовательности загружаются в одну из трех баз данных GenBank [43], ENA [44] или DDBJ [45] либо авторами, либо центрами секвенирования. Между этими тремя базами данных налажен ежедневный обмен данными, так что ежедневные обновления на серверах NCBI, где хранится GenBank, включают в себя самые последние доступные данные о последовательностях из всех трех источников.…”

Section: хранение и обмен даннымиunclassified

Big Data in Bioinformatics

Nazipova¹

2017

Math.Biol.Bioinf.

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Аннотация. Секвенирование человеческого генома началось в 1994 году. Понадобилось 10 лет работы многих научных коллективов для того, чтобы получить черновую последовательность ДНК человека. Современные технологии секвенирования позволяют получать геном конкретного человека за несколько дней. Обсуждаются успехи современной биоинформатики, связанные с появлением высокопроизводительных платформ секвенирования, которые не только способствовали расширению возможностей различных направлений биологии и других смежных наук, но и породили феномен больших данных. Обосновывается необходимость разработки новых технологий и методов для организации хранения, управления, анализа и визуализации больших данных. Современная биоинформатика столкнулась не только с проблемой больших данных, но и с огромным разнообразием методов обработки и представления, одновременным существованием различных программных средств и форматов данных. Обсуждаются пути решения возникших проблем, в частности путем использования наработок работы с большими данными из других областей современной жизни, таких как сетевой анализ и анализ деловых данных. Новые системы управления базами данных, отличные от реляционных, помогут решить проблему хранения больших данных и обеспечения приемлемого времени выполнения поисковых запросов. Новые технологии программирования, такие, как обобщенное программирование и визуальное программирование призваны решить проблему разнообразия форматов геномных данных и обеспечить возможность оперативного создания собственных скриптов для обработки данных.

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The EMBL data library

Cited by 94 publications

References 0 publications

Detection of dsRNA-binding domains in RNA helicase A andDrosophilamaleless: implications for monomeric RNA helicases

Detection of dsRNA-binding domains in RNA helicase A andDrosophilamaleless: implications for monomeric RNA helicases

Ribosome‐mediated translational pause and protein domain organization

Big Data in Bioinformatics

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