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17 Publications visible to you, out of a total of 17

Abstract (Expand)

In addition to the ubiquitous big data, one key challenge indata processing and management in the life sciences is the diversity ofsmall data. Diverse pieces of small data have to be transformed intostandards-compliant data. Here, the challenge lies not in the difficulty ofsingle steps that need to be performed, but rather in the fact that manytransformation tasks are to be performed once or only a few times. Thislimits the time that can be put into automated approaches, which inturn severely limits the verifiability of such transformations.As much of the data to be processed is stored in spreadsheets, withinthis paper we justify and propose a lightweight recording-based solutionthat works on a wide variety of spreadsheet programs, from MicrosoftExcel to Google Docs.

Authors: Wolfgang Müller, Lukrécia Mertová

Date Published: 23rd Mar 2023

Publication Type: Journal

Abstract

Not specified

Authors: Ghadeer Mobasher, Wolfgang Müller, Olga Krebs, Michael Gertz

Date Published: 2023

Publication Type: InProceedings

Abstract (Expand)

Chemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the ‘Chemical Identification’ task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.

Authors: Ghadeer Mobasher, Lukrécia Mertová, Sucheta Ghosh, Olga Krebs, Bettina Heinlein, Wolfgang Müller

Date Published: 11th Nov 2021

Publication Type: Proceedings

Abstract

Not specified

Authors: Helge Hass, Carolin Loos, Elba Raimúndez-Álvarez, Jens Timmer, Jan Hasenauer, Clemens Kreutz

Date Published: 1st Sep 2019

Publication Type: Journal

Abstract (Expand)

2-Amino-benzo[ d]thiazole was identified as a new scaffold for the development of improved pteridine reductase-1 (PTR1) inhibitors and anti-trypanosomatidic agents. Molecular docking and crystallography guided the design and synthesis of 42 new benzothiazoles. The compounds were assessed for Trypanosoma brucei and Leishmania major PTR1 inhibition and in vitro activity against T. brucei and amastigote Leishmania infantum. We identified several 2-amino-benzo[ d]thiazoles with improved enzymatic activity ( TbPTR1 IC50 = 0.35 muM; LmPTR1 IC50 = 1.9 muM) and low muM antiparasitic activity against T. brucei. The ten most active compounds against TbPTR1 were able to potentiate the antiparasitic activity of methotrexate when evaluated in combination against T. brucei, with a potentiating index between 1.2 and 2.7. The compound library was profiled for early ADME toxicity, and 2-amino- N-benzylbenzo[ d]thiazole-6-carboxamide (4c) was finally identified as a novel potent, safe, and selective anti-trypanocydal agent (EC50 = 7.0 muM). Formulation of 4c with hydroxypropyl-beta-cyclodextrin yielded good oral bioavailability, encouraging progression to in vivo studies.

Authors: P. Linciano, C. Pozzi, L. D. Iacono, F. di Pisa, G. Landi, A. Bonucci, S. Gul, M. Kuzikov, B. Ellinger, G. Witt, N. Santarem, C. Baptista, C. Franco, C. B. Moraes, W. Muller, U. Wittig, R. Luciani, A. Sesenna, A. Quotadamo, S. Ferrari, I. Pohner, A. Cordeiro-da-Silva, S. Mangani, L. Costantino, M. P. Costi

Date Published: 25th Apr 2019

Publication Type: Journal

Abstract (Expand)

According to the World Health Organization, more than 1 billion people are at risk of or are affected by neglected tropical diseases. Examples of such diseases include trypanosomiasis, which causes sleeping sickness; leishmaniasis; and Chagas disease, all of which are prevalent in Africa, South America, and India. Our aim within the New Medicines for Trypanosomatidic Infections project was to use (1) synthetic and natural product libraries, (2) screening, and (3) a preclinical absorption, distribution, metabolism, and excretion-toxicity (ADME-Tox) profiling platform to identify compounds that can enter the trypanosomatidic drug discovery value chain. The synthetic compound libraries originated from multiple scaffolds with known antiparasitic activity and natural products from the Hypha Discovery MycoDiverse natural products library. Our focus was first to employ target-based screening to identify inhibitors of the protozoan Trypanosoma brucei pteridine reductase 1 ( TbPTR1) and second to use a Trypanosoma brucei phenotypic assay that made use of the T. brucei brucei parasite to identify compounds that inhibited cell growth and caused death. Some of the compounds underwent structure-activity relationship expansion and, when appropriate, were evaluated in a preclinical ADME-Tox assay panel. This preclinical platform has led to the identification of lead-like compounds as well as validated hits in the trypanosomatidic drug discovery value chain.

Authors: C. B. Moraes, G. Witt, M. Kuzikov, B. Ellinger, T. Calogeropoulou, K. C. Prousis, S. Mangani, F. Di Pisa, G. Landi, L. D. Iacono, C. Pozzi, L. H. Freitas-Junior, B. Dos Santos Pascoalino, C. P. Bertolacini, B. Behrens, O. Keminer, J. Leu, M. Wolf, J. Reinshagen, A. Cordeiro-da-Silva, N. Santarem, A. Venturelli, S. Wrigley, D. Karunakaran, B. Kebede, I. Pohner, W. Muller, J. Panecka-Hofman, R. C. Wade, M. Fenske, J. Clos, J. M. Alunda, M. J. Corral, E. Uliassi, M. L. Bolognesi, P. Linciano, A. Quotadamo, S. Ferrari, M. Santucci, C. Borsari, M. P. Costi, S. Gul

Date Published: 21st Feb 2019

Publication Type: Journal

Abstract (Expand)

SABIO-RK (http://sabiork.h-its.org/) is a manually curated database containing data about biochemical reactions and their reaction kinetics. The data are primarily extracted from scientific literature and stored in a relational database. The content comprises both naturally occurring and alternatively measured biochemical reactions and is not restricted to any organism class. The data are made available to the public by a web-based search interface and by web services for programmatic access. In this update we describe major improvements and extensions of SABIO-RK since our last publication in the database issue of Nucleic Acid Research (2012). (i) The website has been completely revised and (ii) allows now also free text search for kinetics data. (iii) Additional interlinkages with other databases in our field have been established; this enables users to gain directly comprehensive knowledge about the properties of enzymes and kinetics beyond SABIO-RK. (iv) Vice versa, direct access to SABIO-RK data has been implemented in several systems biology tools and workflows. (v) On request of our experimental users, the data can be exported now additionally in spreadsheet formats. (vi) The newly established SABIO-RK Curation Service allows to respond to specific data requirements.

Authors: U. Wittig, M. Rey, A. Weidemann, R. Kania, W. Muller

Date Published: 4th Jan 2018

Publication Type: Journal

Abstract (Expand)

Pteridine reductase-1 (PTR1) is a promising drug target for the treatment of trypanosomiasis. We investigated the potential of a previously identified class of thiadiazole inhibitors of Leishmania major PTR1 for activity against Trypanosoma brucei (Tb). We solved crystal structures of several TbPTR1-inhibitor complexes to guide the structure-based design of new thiadiazole derivatives. Subsequent synthesis and enzyme- and cell-based assays confirm new, mid-micromolar inhibitors of TbPTR1 with low toxicity. In particular, compound 4m, a biphenyl-thiadiazole-2,5-diamine with IC50 = 16 muM, was able to potentiate the antitrypanosomal activity of the dihydrofolate reductase inhibitor methotrexate (MTX) with a 4.1-fold decrease of the EC50 value. In addition, the antiparasitic activity of the combination of 4m and MTX was reversed by addition of folic acid. By adopting an efficient hit discovery platform, we demonstrate, using the 2-amino-1,3,4-thiadiazole scaffold, how a promising tool for the development of anti-T. brucei agents can be obtained.

Authors: P. Linciano, A. Dawson, I. Pohner, D. M. Costa, M. S. Sa, A. Cordeiro-da-Silva, R. Luciani, S. Gul, G. Witt, B. Ellinger, M. Kuzikov, P. Gribbon, J. Reinshagen, M. Wolf, B. Behrens, V. Hannaert, P. A. M. Michels, E. Nerini, C. Pozzi, F. di Pisa, G. Landi, N. Santarem, S. Ferrari, P. Saxena, S. Lazzari, G. Cannazza, L. H. Freitas-Junior, C. B. Moraes, B. S. Pascoalino, L. M. Alcantara, C. P. Bertolacini, V. Fontana, U. Wittig, W. Muller, R. C. Wade, W. N. Hunter, S. Mangani, L. Costantino, M. P. Costi

Date Published: 30th Sep 2017

Publication Type: Journal

Abstract

Not specified

Authors: Wolfgang Müller, Meik Bittkowski, Martin Golebiewski, Renate Kania, Maja Rey, Andreas Weidemann, Ulrike Wittig

Date Published: 1st Mar 2017

Publication Type: Journal

Abstract (Expand)

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.

Authors: K. Wolstencroft, O. Krebs, J. L. Snoep, N. J. Stanford, F. Bacall, M. Golebiewski, R. Kuzyakiv, Q. Nguyen, S. Owen, S. Soiland-Reyes, J. Straszewski, D. D. van Niekerk, A. R. Williams, L. Malmstrom, B. Rinn, W. Muller, C. Goble

Date Published: 4th Jan 2017

Publication Type: Journal

Abstract (Expand)

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.

Authors: K. Wolstencroft, O. Krebs, J. L. Snoep, N. J. Stanford, F. Bacall, M. Golebiewski, R. Kuzyakiv, Q. Nguyen, S. Owen, S. Soiland-Reyes, J. Straszewski, D. D. van Niekerk, A. R. Williams, L. Malmstrom, B. Rinn, W. Muller, C. Goble

Date Published: 4th Jan 2017

Publication Type: Journal

Abstract (Expand)

Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.

Authors: D. Nickerson, K. Atalag, B. de Bono, J. Geiger, C. Goble, S. Hollmann, J. Lonien, W. Muller, B. Regierer, N. J. Stanford, M. Golebiewski, P. Hunter

Date Published: 7th Apr 2016

Publication Type: Not specified

Abstract (Expand)

In systems biology, quantitative experimental data is the basis of building mathematical models. In most of the cases, they are stored in Excel files and hosted locally. To have a public database for collecting, retrieving and citing experimental raw data as well as experimental conditions is important for both experimentalists and modelers. However, the great effort needed in the data handling procedure and in the data submission procedure becomes the crucial limitation for experimentalists to contribute to a database, thereby impeding the database to deliver its benefit. Moreover, manual copy and paste operations which are commonly used in those procedures increase the chance of making mistakes. Excemplify, a web-based application, proposes a flexible and adaptable template-based solution to solve these problems. Comparing to the normal template based uploading approach, which is supported by some public databases, rather than predefining a format that is potentiall impractical, Excemplify allows users to create their own experiment-specific content templates in different experiment stages and to build corresponding knowledge bases for parsing. Utilizing the embedded knowledge of used templates, Excemplify is able to parse experimental data from the initial setup stage and generate following stages spreadsheets automatically. The proposed solution standardizes the flows of data traveling according to the standard procedures of applying the experiment, cuts down the amount of manual effort and reduces the chance of mistakes caused by manual data handling. In addition, it maintains the context of meta-data from the initial preparation manuscript and improves the data consistency. It interoperates and complements RightField and SEEK as well.

Authors: L. Shi, L. Jong, U. Wittig, P. Lucarelli, M. Stepath, S. Mueller, L. A. D'Alessandro, U. Klingmuller, W. Muller

Date Published: 3rd Apr 2013

Publication Type: Journal

Abstract (Expand)

The increase in volume and complexity of biological data has led to increased requirements to reuse that data. Consistent and accurate metadata is essential for this task, creating new challenges in semantic data annotation and in the constriction of terminologies and ontologies used for annotation. The BioSharing community are developing standards and terminologies for annotation, which have been adopted across bioinformatics, but the real challenge is to make these standards accessible to laboratory scientists. Widespread adoption requires the provision of tools to assist scientists whilst reducing the complexities of working with semantics. This paper describes unobtrusive ‘stealthy’ methods for collecting standards compliant, semantically annotated data and for contributing to ontologies used for those annotations. Spreadsheets are ubiquitous in laboratory data management. Our spreadsheet-based RightField tool enables scientists to structure information and select ontology terms for annotation within spreadsheets, producing high quality, consistent data without changing common working practices. Furthermore, our Populous spreadsheet tool proves effective for gathering domain knowledge in the form of Web Ontology Language (OWL) ontologies. Such a corpus of structured and semantically enriched knowledge can be extracted in Resource Description Framework (RDF), providing further means for searching across the content and contributing to Open Linked Data (http://linkeddata.org/)

Authors: , , Matthew Horridge, Simon Jupp, , , , , Robert Stevens,

Date Published: 1st Feb 2013

Publication Type: Journal

Abstract (Expand)

RightField is a Java application that provides a mechanism for embedding ontology annotation support for scientific data in Microsoft Excel or Open Office spreadsheets. The result is semantic annotation by stealth, with an annotation process that is less error-prone, more efficient, and more consistent with community standards. By automatically generating RDF statements for each cell a rich, Linked Data querying environment allows scientists to search their data and other Linked Data resources interchangeably, and caters for queries across heterogeneous spreadsheets. RightField has been developed for Systems Biologists but has since adopted more widely. It is open source (BSD license) and freely available from http://www.rightfield.org.uk

Authors: Katy Wolstencroft, Stuart Owen, Matthew Horridge, Wolfgang Mueller, Finn Bacall, Jacky Snoep, Franco du Preez, Quyen Nguyen, Olga Krebs, Carole Goble

Date Published: 2012

Publication Type: Journal

Abstract (Expand)

SABIO-RK (http://sabio.h-its.org/) is a web-accessible database storing comprehensive information about biochemical reactions and their kinetic properties. SABIO-RK offers standardized data manually extracted from the literature and data directly submitted from lab experiments. The database content includes kinetic parameters in relation to biochemical reactions and their biological sources with no restriction on any particular set of organisms. Additionally, kinetic rate laws and corresponding equations as well as experimental conditions are represented. All the data are manually curated and annotated by biological experts, supported by automated consistency checks. SABIO-RK can be accessed via web-based user interfaces or automatically via web services that allow direct data access by other tools. Both interfaces support the export of the data together with its annotations in SBML (Systems Biology Markup Language), e.g. for import in modelling tools.

Authors: Ulrike Wittig, , Martin Golebiewski, , Lei Shi, Lenneke Jong, Enkhjargal Algaa, Andreas Weidemann, Heidrun Sauer-Danzwith, Saqib Mir, , Meik Bittkowski, Elina Wetsch, ,

Date Published: 22nd Nov 2011

Publication Type: Journal

Abstract (Expand)

MOTIVATION: In the Life Sciences, guidelines, checklists and ontologies describing what metadata is required for the interpretation and reuse of experimental data are emerging. Data producers, however, may have little experience in the use of such standards and require tools to support this form of data annotation. RESULTS: RightField is an open source application that provides a mechanism for embedding ontology annotation support for Life Science data in Excel spreadsheets. Individual cells, columns or rows can be restricted to particular ranges of allowed classes or instances from chosen ontologies. The RightField-enabled spreadsheet presents selected ontology terms to the users as a simple drop-down list, enabling scientists to consistently annotate their data. The result is 'semantic annotation by stealth', with an annotation process that is less error-prone, more efficient, and more consistent with community standards. AVAILABILITY AND IMPLEMENTATION: RightField is open source under a BSD license and freely available from http://www.rightfield.org.uk

Authors: , , Matthew Horridge, , , , ,

Date Published: 15th Jul 2011

Publication Type: Journal

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