SELEX_DB: an activated database on selected randomized DNA/RNA sequences addressed to genomic sequence annotation

Ponomarenko, Julia; Orlova, Galina; Пономаренко, М. П.; Lavryushev, Sergey V.; Frolov, Anatoly S.; Zybova, Svetlana V.; Kolchanov, Nikolay А.

doi:10.1093/nar/28.1.205

Cited by 22 publications

(10 citation statements)

References 48 publications

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“…The experimental data includes three dimensional (3D) structures of TFs bound to DNA, immunoprecipitated DNA sequences followed by hybridization to microarray chips (ChIP-chip) [4] or massively parallel sequencing (ChIP-Seq) [5], Systematic Evolution of Ligands by EXponential enrichment (SELEX) [6], [7], or protein-binding microarrays (PBMs) [8]. While each of these methods have proven to be useful, they each have their own drawbacks.…”

Section: Introductionmentioning

confidence: 99%

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

Schones

Wang

et al. 2013

PLoS ONE

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Scanning through genomes for potential transcription factor binding sites (TFBSs) is becoming increasingly important in this post-genomic era. The position weight matrix (PWM) is the standard representation of TFBSs utilized when scanning through sequences for potential binding sites. However, many transcription factor (TF) motifs are short and highly degenerate, and methods utilizing PWMs to scan for sites are plagued by false positives. Furthermore, many important TFs do not have well-characterized PWMs, making identification of potential binding sites even more difficult. One approach to the identification of sites for these TFs has been to use the 3D structure of the TF to predict the DNA structure around the TF and then to generate a PWM from the predicted 3D complex structure. However, this approach is dependent on the similarity of the predicted structure to the native structure. We introduce here a novel approach to identify TFBSs utilizing structure information that can be applied to TFs without characterized PWMs, as long as a 3D complex structure (TF/DNA) exists. This approach utilizes an energy function that is uniquely trained on each structure. Our approach leads to increased prediction accuracy and robustness compared with those using a more general energy function. The software is freely available upon request.

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Section: Introductionmentioning

confidence: 99%

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

Schones

Wang

et al. 2013

PLoS ONE

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“…Sequence length was 60 bp. The samples of the other BSs (AP1, C/EBP, E2F, GATA1, GR, HNF1, HNF3, HNF4, MyoD, NF-Y, OCT1, SF1, Sp1, and TATA-box) were partly taken from the TRRD, partly from the SELEX databases [22]. The recognition methods of all the BSs were built as described below.…”

Section: Methodsmentioning

confidence: 99%

Recognition of interferon-inducible sites, promoters, and enhancers

et al. 2007

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Background: Computational analysis of gene regulatory regions is important for prediction of functions of many uncharacterized genes. With this in mind, search of the target genes for interferon (IFN) induction appears of interest. IFNs are multi-functional cytokines. Their effects are immunomodulatory, antiviral, antibacterial, and antitumor. The interaction of the IFNs with their cell surface receptors produces an activation of several transcription factors. Four regulatory factors, ISGF3, STAT1, IRF1, and NF-κB, are essential for the function of the IFN system. The aim of this work is the development of computational approaches for the recognition of DNA binding sites for these factors and computer programs for the prediction of the IFN-inducible regions.

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“…The trace identifiers given by the NCBI will be cross-referenced within the clone insert sequence entries. Currently, the experiment entries contain cross-references to Swiss-Prot, EMBL (vector sequence), REBASE ( 12 ), SELEX_DB ( 4 ) and TRANSFAC ( 5 ).…”

Section: Relationship To Other Databasesmentioning

confidence: 99%

“…In contrast, smaller SELEX sequence collections obtained with conventional methods have traditionally been disseminated through the journal literature. SELEX_DB ( 4 ) and TRANSFAC ( 5 ) are databases which offer these data in machine-readable form. Other related databases, such as JASPAR ( 6 ), only distribute the SELEX-based computational models (weight matrices) of transcription factor binding sites, but not the SELEX sequences from which these models were derived.…”

Section: Introductionmentioning

confidence: 99%

HTPSELEX--a database of high-throughput SELEX libraries for transcription factor binding sites

Jagannathan

Roulet

Delorenzi

et al. 2006

Nucleic Acids Research

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HTPSELEX is a public database providing access to primary and derived data from high-throughput SELEX experiments aimed at characterizing the binding specificity of transcription factors. The resource is primarily intended to serve computational biologists interested in building models of transcription factor binding sites from large sets of binding sequences. The guiding principle is to make available all information that is relevant for this purpose. For each experiment, we try to provide accurate information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, assembled clone sequences (concatemers) and complete sets of in vitro selected protein-binding tags. In addition, we offer in-house derived binding sites models. HTPSELEX also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols. The FTP site contains the trace archives and database flatfiles. The web server offers user-friendly interfaces for viewing individual entries and quality-controlled download of SELEX sequence libraries according to a user-defined sequencing quality threshold. HTPSELEX is available from and .

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SELEX_DB: an activated database on selected randomized DNA/RNA sequences addressed to genomic sequence annotation

Cited by 22 publications

References 48 publications

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

Recognition of interferon-inducible sites, promoters, and enhancers

HTPSELEX--a database of high-throughput SELEX libraries for transcription factor binding sites

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