Ines Liebich

Bio: Ines Liebich is an academic researcher. The author has contributed to research in topics: TRANSFAC & Transcription Factor Gene. The author has an hindex of 7, co-authored 10 publications receiving 4515 citations.

TRANSFAC® and its module TRANSCompel®: transcriptional gene regulation in eukaryotes

Abstract: The TRANSFAC database on transcription factors, their binding sites, nucleotide distribution matrices and regulated genes as well as the complementing database TRANSCompel on composite elements have been further enhanced on various levels. A new web interface with different search options and integrated versions of Match and Patch provides increased functionality for TRANSFAC. The list of databases which are linked to the common GENE table of TRANSFAC and TRANSCompel has been extended by: Ensembl, UniGene, EntrezGene, HumanPSD and TRANSPRO. Standard gene names from HGNC, MGI and RGD, are included for human, mouse and rat genes, respectively. With the help of InterProScan, Pfam, SMART and PROSITE domains are assigned automatically to the protein sequences of the transcription factors. TRANSCompel contains now, in addition to the COMPEL table, a separate table for detailed information on the experimental EVIDENCE on which the composite elements are based. Finally, for TRANSFAC, in respect of data growth, in particular the gain of Drosophila transcription factor binding sites (by courtesy of the Drosophila DNase I footprint database) and of Arabidopsis factors (by courtesy of DATF, Database of Arabidopsis Transcription Factors) has to be stressed. The here described public releases, TRANSFAC 7.0 and TRANSCompel 7.0, are accessible under http://www.gene-regulation.com/pub/databases.html.

TRANSFAC: an integrated system for gene expression regulation

Abstract: TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles (http://transfac.gbf.de/TRANSFAC/ ). Its content has been enhanced, in particular by information about training sequences used for the construction of nucleotide matrices as well as by data on plant sites and factors. Moreover, TRANSFAC has been extended by two new modules: PathoDB provides data on pathologically relevant mutations in regulatory regions and transcription factor genes, whereas S/MARt DB compiles features of scaffold/matrix attached regions (S/MARs) and the proteins binding to them. Additionally, the databases TRANSPATH, about signal transduction, and CYTOMER, about organs and cell types, have been extended and are increasingly integrated with the TRANSFAC data sources.

The TRANSFAC system on gene expression regulation.

Abstract: The TRANSFAC database on transcription factors and their DNA-binding sites and profiles (http://www.gene-regulation.de/) has been quantitatively extended and supplemented by a number of modules. These modules give information about pathologically relevant mutations in regulatory regions and transcription factor genes (PathoDB), scaffold/matrix attached regions (S/MARt DB), signal transduction (TRANSPATH) and gene expression sources (CYTOMER). Altogether, these distinct database modules constitute the TRANSFAC system. They are accompanied by a number of program routines for identifying potential transcription factor binding sites or for localizing individual components in the regulatory network of a cell.

Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms

Abstract: TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles. In addition to being updated and extended by new features, it has been complemented now by a series of additional database modules. Among them, modules which provide data about signal transduction pathways (TRANSPATH) or about cell types/organs/developmental stages (CYTOMER) are available as well as an updated version of the previously described COMPEL database. The databases are available on the WWW at http://transfac.gbf.de/

Evaluation of sequence motifs found in scaffold/matrix‐attached regions (S/MARs)

Abstract: Based on the contents of the database S/MARt DB, the most comprehensive data collection of scaffold/matrix-attached regions (S/MARs) publicly available thus far, we initiated a systematic evaluation of the stored data. By analyzing the 245 S/MAR sequences presently described in this database, we found that the S/MARs contained in this collection are generally AT-rich, with certain significant exceptions. Comparative analyses showed that most of the AT-rich motifs which were found to be enriched in S/MARs are also enriched in randomized S/MAR sequences of the same AT content. Some sequence patterns previously suggested to be characteristic for S/MARs were also investigated, among them potential binding sites for homeodomain transcription factors. Even though hexanucleotides containing the core motif of homeodomain factors were frequently observed in S/MARs, only a few potential binding sites for these factors were found enriched when compared with regulatory regions or exon sequences. All our analyses indicated that, on average, the observed frequency of motifs in S/MAR elements is largely influenced by the AT content. Our results can serve as a guideline for further improvements in the definition of S/MARs, which are now believed to constitute the functional coordinate system for genomic regulatory regions.

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

Abstract: Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

Abstract: We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

Enrichr: Interactive and collaborative HTML5 gene list enrichment analysis tool

Abstract: System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr .

An automated method for finding molecular complexes in large protein interaction networks.

Abstract: Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from ftp://ftp.mshri.on.ca/pub/BIND/Tools/MCODE .