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Szymon M Kielbasa

Publications and source records attributed to Szymon M Kielbasa.

3 recordsLinked to original sources

Measuring similarities between transcription factor binding sites.

BACKGROUND: Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites. RESULTS: We propose to identify and group similar profiles using two independent similarity measures: chi2 distances between position frequency matrices (PFMs) and correlation coefficients between position weight matrices (PWMs) scores. CONCLUSION: We show that these measures complement each other and allow to associate Jaspar and Transfac matrices. Clusters of highly similar matrices are identified and can be used to optimise the search for regulatory elements. Moreover, the application of the measures is illustrated by assigning E-box matrices of a SELEX experiment and of experimentally characterised binding sites of circadian clock genes to the Myc-Max cluster.

ARNTL Transcription Factors↗

HuSiDa--the human siRNA database: an open-access database for published functional siRNA sequences and technical details of efficient transfer into recipient cells.

Small interfering RNAs (siRNAs) have become a standard tool in functional genomics. Once incorporated into the RNA-induced silencing complex (RISC), siRNAs mediate the specific recognition of corresponding target mRNAs and their cleavage. However, only a small fraction of randomly chosen siRNA sequences is able to induce efficient gene silencing. In common laboratory practice, successful RNA interference experiments typically require both, the labour and cost-intensive identification of an active siRNA sequence and the optimization of target cell line-specific procedures for optimal siRNA delivery. To optimize the design and performance of siRNA experiments, we have established the human siRNA database (HuSiDa). The database provides sequences of published functional siRNA molecules targeting human genes and important technical details of the corresponding gene silencing experiments, including the mode of siRNA generation, recipient cell lines, transfection reagents and procedures and direct links to published references (PubMed). The database can be accessed at http://www.human-siRNA-database.net. We used the siRNA sequence information stored in the database for scrutinizing published sequence selection parameters for efficient gene silencing.

Base Sequence↗

SeqVISTA: a new module of integrated computational tools for studying transcriptional regulation.

Transcriptional regulation is one of the most basic regulatory mechanisms in the cell. The accumulation of multiple metazoan genome sequences and the advent of high-throughput experimental techniques have motivated the development of a large number of bioinformatics methods for the detection of regulatory motifs. The regulatory process is extremely complex and individual computational algorithms typically have very limited success in genome-scale studies. Here, we argue the importance of integrating multiple computational algorithms and present an infrastructure that integrates eight web services covering key areas of transcriptional regulation. We have adopted the client-side integration technology and built a consistent input and output environment with a versatile visualization tool named SeqVISTA. The infrastructure will allow for easy integration of gene regulation analysis software that is scattered over the Internet. It will also enable bench biologists to perform an arsenal of analysis using cutting-edge methods in a familiar environment and bioinformatics researchers to focus on developing new algorithms without the need to invest substantial effort on complex pre- or post-processors. SeqVISTA is freely available to academic users and can be launched online at http://zlab.bu.edu/SeqVISTA/web.jnlp, provided that Java Web Start has been installed. In addition, a stand-alone version of the program can be downloaded and run locally. It can be obtained at http://zlab.bu.edu/SeqVISTA.

Algorithms↗