References of "Schneider, Reinhard 50003033"
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See detailjClust: a clustering and visualization toolbox
Pavlopoulos, Georgios A.; Moschopoulos, Charalampos N.; Hooper, Sean D. et al

in Bioinformatics (2009), 25(15), 1994-1996

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is ... [more ▼]

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is combined with an advanced implementation of the Medusa interactive visualization module. These implemented algorithms are k-Means, Affinity propagation, Bron-Kerbosch, MULIC, Restricted neighborhood search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut, outside-inside, best neighbors and density control operations. The combination of a simple input. le format, a set of clustering and filtering algorithms linked together with the visualization tool provides a powerful tool for data analysis and information extraction. [less ▲]

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See detailNew in protein structure and function annotation: Hotspots, single nucleotide polymorphisms and the 'Deep Web'
Bromberg, Yana; Yachdav, Guy; Ofran, Yanay et al

in Current Opinion in Drug Discovery & Development (2009), 12(3), 408-419

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of ... [more ▼]

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation. [less ▲]

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See detailOnTheFly: a tool for automated document-based text annotation, data linking and network generation
Pavlopoulos, Georgios A.; Pafilis, Evangelos; Kuhn, M. et al

in Bioinformatics (2009), 25(7), 977-978

OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then ... [more ▼]

OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database. [less ▲]

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See detailGIBA: a clustering tool for detecting protein complexes
Moschopoulos, Charalampos N.; Pavlopoulos, Georgios A.; Schneider, Reinhard UL et al

in BMC Bioinformatics (2009), 10

Background: During the last years, high throughput experimental methods have been developed which generate large datasets of protein - protein interactions (PPIs). However, due to the experimental ... [more ▼]

Background: During the last years, high throughput experimental methods have been developed which generate large datasets of protein - protein interactions (PPIs). However, due to the experimental methodologies these datasets contain errors mainly in terms of false positive data sets and reducing therefore the quality of any derived information. Typically these datasets can be modeled as graphs, where vertices represent proteins and edges the pairwise PPIs, making it easy to apply automated clustering methods to detect protein complexes or other biological significant functional groupings. Methods: In this paper, a clustering tool, called GIBA (named by the first characters of its developers' nicknames), is presented. GIBA implements a two step procedure to a given dataset of protein-protein interaction data. First, a clustering algorithm is applied to the interaction data, which is then followed by a filtering step to generate the final candidate list of predicted complexes. Results: The efficiency of GIBA is demonstrated through the analysis of 6 different yeast protein interaction datasets in comparison to four other available algorithms. We compared the results of the different methods by applying five different performance measurement metrices. Moreover, the parameters of the methods that constitute the filter have been checked on how they affect the final results. Conclusion: GIBA is an effective and easy to use tool for the detection of protein complexes out of experimentally measured protein - protein interaction networks. The results show that GIBA has superior prediction accuracy than previously published methods. [less ▲]

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See detailReflect: augmented browsing for the life scientist
Pafilis, Evangelos; O'Donoghue, Sean I.; Jensen, Lars J. et al

in Nature Biotechnology (2009), 27(6), 508-510

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See detailClustering of cognate proteins among distinct proteomes derived from multiple links to a single seed sequence.
Barbosa Da Silva, Adriano UL; Satagopam, Venkata UL; Schneider, Reinhard UL et al

in BMC bioinformatics (2008), 9

BACKGROUND: Modern proteomes evolved by modification of pre-existing ones. It is extremely important to comparative biology that related proteins be identified as members of the same cognate group, since ... [more ▼]

BACKGROUND: Modern proteomes evolved by modification of pre-existing ones. It is extremely important to comparative biology that related proteins be identified as members of the same cognate group, since a characterized putative homolog could be used to find clues about the function of uncharacterized proteins from the same group. Typically, databases of related proteins focus on those from completely-sequenced genomes. Unfortunately, relatively few organisms have had their genomes fully sequenced; accordingly, many proteins are ignored by the currently available databases of cognate proteins, despite the high amount of important genes that are functionally described only for these incomplete proteomes. RESULTS: We have developed a method to cluster cognate proteins from multiple organisms beginning with only one sequence, through connectivity saturation with that Seed sequence. We show that the generated clusters are in agreement with some other approaches based on full genome comparison. CONCLUSION: The method produced results that are as reliable as those produced by conventional clustering approaches. Generating clusters based only on individual proteins of interest is less time consuming than generating clusters for whole proteomes. [less ▲]

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See detailArena3D: visualization of biological networks in 3D
Pavlopoulos, Georgios A.; O'Donoghue, Sean I.; Satagopam, Venkata UL et al

in BMC Systems Biology (2008), 2

Background: Complexity is a key problem when visualizing biological networks; as the number of entities increases, most graphical views become incomprehensible. Our goal is to enable many thousands of ... [more ▼]

Background: Complexity is a key problem when visualizing biological networks; as the number of entities increases, most graphical views become incomprehensible. Our goal is to enable many thousands of entities to be visualized meaningfully and with high performance. Results: We present a new visualization tool, Arena3D, which introduces a new concept of staggered layers in 3D space. Related data - such as proteins, chemicals, or pathways - can be grouped onto separate layers and arranged via layout algorithms, such as Fruchterman-Reingold, distance geometry, and a novel hierarchical layout. Data on a layer can be clustered via k-means, affinity propagation, Markov clustering, neighbor joining, tree clustering, or UPGMA ('unweighted pair-group method with arithmetic mean'). A simple input format defines the name and URL for each node, and defines connections or similarity scores between pairs of nodes. The use of Arena3D is illustrated with datasets related to Huntington's disease. Conclusion: Arena3D is a user friendly visualization tool that is able to visualize biological or any other network in 3D space. It is free for academic use and runs on any platform. It can be downloaded or lunched directly from http://arena3d.org. Java3D library and Java 1.5 need to be pre-installed for the software to run. [less ▲]

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See detailA survey of visualization tools for biological network analysis.
Pavlopoulos, Georgios A.; Wegener, A. L.; Schneider, Reinhard UL

in BioData Mining (2008)

The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their ... [more ▼]

The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their heterogeneity provides a challenge for the visualization of the data. There are a wide variety of graph representations available, which most often map the data on 2D graphs to visualize biological interactions. These methods are applicable to a wide range of problems, nevertheless many of them reach a limit in terms of user friendliness when thousands of nodes and connections have to be analyzed and visualized. In this study we are reviewing visualization tools that are currently available for visualization of biological networks mainly invented in the latest past years. We comment on the functionality, the limitations and the specific strengths of these tools, and how these tools could be further developed in the direction of data integration and information sharing. [less ▲]

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See detailSuperTarget and Matador: resources for exploring drug-target relationships
Guenther, Stefan; Kuhn, Michael; Dunkel, Mathias et al

in Nucleic Acids Research (2008), 36(SI), 919-922

The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical ... [more ▼]

The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de. [less ▲]

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See detailDevelopment of SRS.php, a Simple Object Access Protocol-based library for data acquisition from integrated biological databases.
Barbosa Da Silva, Adriano UL; Pafilis, E.; Ortega, J. M. et al

in Genetics & Molecular Research [=GMR] (2007), 6(4), 1142-1150

Data integration has become an important task for biological database providers. The current model for data exchange among different sources simplifies the manner that distinct information is accessed by ... [more ▼]

Data integration has become an important task for biological database providers. The current model for data exchange among different sources simplifies the manner that distinct information is accessed by users. The evolution of data representation from HTML to XML enabled programs, instead of humans, to interact with biological databases. We present here SRS.php, a PHP library that can interact with the data integration Sequence Retrieval System (SRS). The library has been written using SOAP definitions, and permits the programmatic communication through webservices with the SRS. The interactions are possible by invoking the methods described in WSDL by exchanging XML messages. The current functions available in the library have been built to access specific data stored in any of the 90 different databases (such as UNIPROT, KEGG and GO) using the same query syntax format. The inclusion of the described functions in the source of scripts written in PHP enables them as webservice clients to the SRS server. The functions permit one to query the whole content of any SRS database, to list specific records in these databases, to get specific fields from the records, and to link any record among any pair of linked databases. The case study presented exemplifies the library usage to retrieve information regarding registries of a Plant Defense Mechanisms database. The Plant Defense Mechanisms database is currently being developed, and the proposal of SRS.php library usage is to enable the data acquisition for the further warehousing tasks related to its setup and maintenance. [less ▲]

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See detailStatus of text-mining techniques applied to biomedical text
Erhardt, R. A. A.; Schneider, Reinhard UL; Blaschke, C.

in Drug Discovery Today (2006), 11(7-8), 315-325

Scientific progress is increasingly based on knowledge and information. Knowledge is now recognized as the driver of productivity and economic growth, leading to a new focus on the role of information in ... [more ▼]

Scientific progress is increasingly based on knowledge and information. Knowledge is now recognized as the driver of productivity and economic growth, leading to a new focus on the role of information in the decision-making process. Most scientific knowledge is registered in publications and other unstructured representations that make it difficult to use and to integrate the information with other sources (e.g. biological databases). Making a computer understand human language has proven to be a complex achievement, but there are techniques capable of detecting, distinguishing and extracting a limited number of different classes of facts. In the biomedical field, extracting information has specific problems: complex and ever-changing nomenclature (especially genes and proteins) and the limited representation of domain knowledge. [less ▲]

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See detailForeword
Schneider, Reinhard UL; Voss, H.

in In Silico Technologies in Drug Target Identification and Validation (2006)

The pharmaceutical industry relies on numerous well-designed experiments involving high-throughput techniques and in silico approaches to analyze potential drug targets. These in silico methods are often ... [more ▼]

The pharmaceutical industry relies on numerous well-designed experiments involving high-throughput techniques and in silico approaches to analyze potential drug targets. These in silico methods are often predictive, yielding faster and less expensive analyses than traditional in vivo or in vitro procedures. In Silico Technologies in Drug Target Identification and Validation addresses the challenge of testing a growing number of new potential targets and reviews currently available in silico approaches for identifying and validating these targets. The book emphasizes computational tools, public and commercial databases, mathematical methods, and software for interpreting complex experimental data. The book describes how these tools are used to visualize a target structure, identify binding sites, and predict behavior. World-renowned researchers cover many topics not typically found in most informatics books, including functional annotation, siRNA design, pathways, text mining, ontologies, systems biology, database management, data pipelining, and pharmacogenomics. Covering issues that range from prescreening target selection to genetic modeling and valuable data integration, In Silico Technologies in Drug Target Identification and Validation is a self-contained and practical guide to the various computational tools that can accelerate the identification and validation stages of drug target discovery and determine the biological functionality of potential targets more effectively. [less ▲]

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See detailEnsemble and UniProt (Swiss-Prot)
Jackson, D.; Schneider, Reinhard UL

in Genomics, Proteomics & Bioinformatics (2005)

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See detailA bioinformatics perspective on proteomics: Data storage, analysis, and integration
Kremer, A.; Schneider, Reinhard UL; Terstappen, G. C.

in Bioscience Reports (2005), 25(1-2), 95-106

The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence ... [more ▼]

The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence, abundance, identity, sequence, structure, properties, and interactions need to be stored. Currently, a common standard has not yet been established and open access to results is needed for further development of robust analysis algorithms. Databases for proteomics will evolve from pure storage into knowledge resources, providing a repository for information (meta-data) which is mainly not stored in simple flat files. This review will shed light on recent steps towards the generation of a common standard in proteomics data storage and integration, but is not meant to be a comprehensive overview of all available databases and tools in the proteomics community. [less ▲]

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See detailBeyond annotation transfer by homology: novel protein-function prediction methods to assist drug discovery
Ofran, Y.; Punta, M.; Schneider, Reinhard UL et al

in Drug Discovery Today (2005), 10(21), 1475-1482

Every entirely sequenced genome reveals 100s to 1000s of protein sequences for which the only annotation available is 'hypothetical protein'. Thus, in the human genome and in the genomes of pathogenic ... [more ▼]

Every entirely sequenced genome reveals 100s to 1000s of protein sequences for which the only annotation available is 'hypothetical protein'. Thus, in the human genome and in the genomes of pathogenic agents there could be 1000s of potential, unexplored drug targets. Computational prediction of protein function can play a role in studying these targets. We shall review the challenges, research approaches and recently developed tools in the field of computational function-prediction and we will discuss the ways these issues can change the process of drug discovery. [less ▲]

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See detailImproving Research Productivity at a Pharmaceutical Company
Ramakrishnan, S.; Caruso, A.; Schneider, Reinhard UL

in LION bioscience AG White Paper (2002)

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See detailINTERPRO
Apweiler, R.; Attwood, T. K.; Bairoch, A. et al

in Bioinformatics (2000)

InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ... [more ▼]

InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Merged annotations from PRINTS, PROSITE and Pfam form the InterPro core. Each combined InterPro entry includes functional descriptions and literature references, and links are made back to the relevant parent database(s), allowing users to see at a glance whether a particular family or domain has associated patterns, profiles, fingerprints, etc.. Merged and individual entries (i.e., those that have no counterpart in the companion resources) are assigned unique accession numbers. The first release of InterPro contains around 2,400 entries, representing families, domains, repeats and sites of post-translational modification (PTMs) encoded by 4,300 regular expressions, profiles, fingerprints and Hidden Markov Models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 370,000 hits in total). The database is accessible for text-based searches at http://www.ebi.ac.uk/ interpro/. [less ▲]

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See detailDatenexplosion erschwert Bioforschung
Schneider, Reinhard UL

in Frankfurter Allgemeine Zeitung (2000)

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See detailBioinformatik: Verloren im Datendschungel ?
Schneider, Reinhard UL

in Nachrichten aus der Chemie : Zeitschrift der Gesellschaft Deutscher Chemiker (2000), 48(5), 622-625

Selbst Insider dürften von der stürmischen Entwicklung der Bioinformatik in den letzten Jahren überrascht worden sein. Die Bioinformatik hat sich dabei von einer „Elfenbeinturm-Wissenschaft“ zu einer ... [more ▼]

Selbst Insider dürften von der stürmischen Entwicklung der Bioinformatik in den letzten Jahren überrascht worden sein. Die Bioinformatik hat sich dabei von einer „Elfenbeinturm-Wissenschaft“ zu einer stark anwendungsorientierten Disziplin entwickelt. Die Hochdurchsatztechnologien und die damit verbundene Quantität an Daten auf der einen Seite und die starke Nachfrage von Seiten der Industrie an einer Auswertung der Daten auf der anderen Seite haben sich als die treibenden Kräfte für den Boom in der Bioinformatik erwiesen. So wird zur Zeit beispielsweise einer der weltweit größten „Supercomputer“, seit Jahrzehnten eher das Feld von Physikern oder Meterologen, bei der Firma Celera installiert, einer Firma die das menschliche Genom entschlüsselt, und „gelernte“ Bioinformatiker sind auf dem Arbeitsmarkt fast so schwer zu finden wie Trüffel im Wald. In diesem kurzen Artikel möchte ich mich auf die derzeitigen und zukünftigen Herausforderungen im Bereich der Life Science Informatik im Rahmen von F+E-Anstrengungen beschränken und den Kernbereich der vielleicht eher akademisch orientierten Bioinformatik, wie die Algorithmenentwicklung für die zahlreichen Vorhersagemethoden und Datenbanksuchen, ausblenden. [less ▲]

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See detailThe HSSP database of protein structure sequence alignments and family profiles
Dodge, C.; Schneider, Reinhard UL; Sander, C.

in Nucleic Acids Research (1998), 26(1), 313-315

HSSP (http://www.sander.embl-ebi.ac.uk/hssp/) is a derived database merging structure (3-D) and sequence (1-D) information, For each protein of known 3D structure from the Protein Data Bank (PDB), we ... [more ▼]

HSSP (http://www.sander.embl-ebi.ac.uk/hssp/) is a derived database merging structure (3-D) and sequence (1-D) information, For each protein of known 3D structure from the Protein Data Bank (PDB), we provide a multiple sequence alignment of putative homologues and a sequence profile characteristic of the protein family, centered on the known structure. The list of homologues is the result of an iterative database search in SWISS-PROT using a position-weighted dynamic programming method for sequence profile alignment (MaxHom). The database is updated frequently, The listed putative homologues are very likely to have the same 3D structure as the PDB protein to which they have been aligned. As a result, the database not only provides aligned sequence families, but also implies secondary and tertiary structures covering 33% of all sequences in SWISS-PROT. [less ▲]

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