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13 results on '"Jarnot, Patryk"'

1. LCR-BLAST—A New Modification of BLAST to Search for Similar Low Complexity Regions in Protein Sequences

Author

Jarnot, Patryk, Ziemska-Legięcka, Joanna, Grynberg, Marcin, Gruca, Aleksandra, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Gruca, Aleksandra, editor, Czachórski, Tadeusz, editor, Deorowicz, Sebastian, editor, Harężlak, Katarzyna, editor, and Piotrowska, Agnieszka, editor

Published
2020
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6. Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases

Author

Tørresen, Ole K., Star, Bastiaan, Mier, Pablo, Andrade-Navarro, Miguel A., Bateman, Alex, Jarnot, Patryk, Gruca, Aleksandra, Grynberg, Marcin, Kajava, Andrey V., Promponas, Vasilis J., Anisimova, Maria, Jakobsen, Kjetill S., Linke, Dirk, Centre de recherche en Biologie Cellulaire (CRBM), Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1), Promponas, Vasilis J. [0000-0003-3352-4831], European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Silesian University of Technology, Biophysics and Bioinformatics Laboratory, Zürich University of Applied Sciences (ZHAW), Max Planck Institute for Developmental Biology, and Max-Planck-Gesellschaft

Subjects
FOS: Computer and information sciences, Bioinformatics, [SDV]Life Sciences [q-bio], Sequence assembly, Genomics, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, Computational biology, Biology, Genome, 03 medical and health sciences, Annotation, 0302 clinical medicine, Tandem repeat, Genetics, Animals, Survey and Summary, Databases, Protein, Gene, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, End user, 572: Biochemie, DNA, Sequence Analysis, DNA, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Workflow, ComputingMethodologies_PATTERNRECOGNITION, Gadus morhua, Tandem Repeat Sequences, Scientific Experimental Error, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Databases, Nucleic Acid, 030217 neurology & neurosurgery
Abstract

The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with ‘ready-to-use’ deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where mis-annotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others.

Published
2019

8. PlaToLoCo: the first web meta-server for visualization and annotation of low complexity regions in proteins

Author

Jarnot, Patryk, primary, Ziemska-Legiecka, Joanna, additional, Dobson, Laszlo, additional, Merski, Matthew, additional, Mier, Pablo, additional, Andrade-Navarro, Miguel A, additional, Hancock, John M, additional, Dosztányi, Zsuzsanna, additional, Paladin, Lisanna, additional, Necci, Marco, additional, Piovesan, Damiano, additional, Tosatto, Silvio C E, additional, Promponas, Vasilis J, additional, Grynberg, Marcin, additional, and Gruca, Aleksandra, additional

Published
2020
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9. Providing Molecular Characterization for Unexplained Adverse Drug Reactions

Author

Calvier, François-Élie, Monnin, Pierre, Boland, Miguel, Jarnot, Patryk, Bresso, Emmanuel, Smaïl-Tabbone, Malika, Coulet, Adrien, Bousquet, Cedric, CHU Saint-Etienne, Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Silesian University of Technology, Computational Algorithms for Protein Structures and Interactions (CAPSID), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Stanford Center for BioMedical Informatics Research (BMIR), Stanford University, Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM), and ANR-15-CE23-0028,PractiKPharma,Confrontation entre connaissances de l'état de l'art et connaissances extraites de dossiers patients en pharmacogénomique(2015)

Subjects
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Feature selection, Machine learning, Adverse drug reaction, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

Podium Abstract at MedInfo 2019, Lyon, France; Mining large drug-oriented knowledge graphs enables predicting Adverse Drug Reactions (ADRs). Indeed, these graphs encompass knowledge elements about the molecular mechanism of drugs (e.g. drug targets, Gene Ontology annotations, gene variations, pathways). However, only few works explored further these graphs in the search for mechanistic explanation for this type of events. We assume that features documenting molecular mechanisms that take part in the prediction are particularly interesting features, since they may provide novel knowledge for the mechanism that may be underlying an ADR. We propose to explore PGxLOD, a knowledge graph built around drugs and pharmacogenomic processes in which they are involved, through the lens of several ADR datasets, each focusing on a particular type of ADRs. Particularly, we propose to use features resulting from the exploration of PGxLOD in a prediction task where best predictive features will be considered as potential elements of explanation.

Published
2019

10. Providing Molecular Characterization for Unexplained Adverse Drug Reactions: Podium Abstract

Author

Calvier, François-Élie, Monnin, Pierre, Boland, Miguel, Jarnot, Patryk, Bresso, Emmanuel, Smaïl-Tabbone, Malika, Coulet, Adrien, Bousquet, Cedric, Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Silesian University of Technology, Computational Algorithms for Protein Structures and Interactions (CAPSID), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Stanford Center for BioMedical Informatics Research (BMIR), Stanford University, Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques [CHU HEGP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Université Paris 13 (UP13)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), ANR-15-CE23-0028,PractiKPharma,Confrontation entre connaissances de l'état de l'art et connaissances extraites de dossiers patients en pharmacogénomique(2015), and CHU Saint-Etienne

Subjects
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Machine learning, Feature selection, Adverse drug reaction, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

Podium Abstract at MedInfo 2019, Lyon, France; Mining large drug-oriented knowledge graphs enables predicting Adverse Drug Reactions (ADRs). Indeed, these graphs encompass knowledge elements about the molecular mechanism of drugs (e.g. drug targets, Gene Ontology annotations, gene variations, pathways). However, only few works explored further these graphs in the search for mechanistic explanation for this type of events. We assume that features documenting molecular mechanisms that take part in the prediction are particularly interesting features, since they may provide novel knowledge for the mechanism that may be underlying an ADR. We propose to explore PGxLOD, a knowledge graph built around drugs and pharmacogenomic processes in which they are involved, through the lens of several ADR datasets, each focusing on a particular type of ADRs. Particularly, we propose to use features resulting from the exploration of PGxLOD in a prediction task where best predictive features will be considered as potential elements of explanation.

Published
2019

11. Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases

Author

Tørresen, Ole K, Star, Bastiaan, Mier, Pablo, Andrade-Navarro, Miguel A, Bateman, Alex, Jarnot, Patryk, Gruca, Aleksandra, Grynberg, Marcin, Kajava, Andrey V, Promponas, Vasilis J, Anisimova, Maria, Jakobsen, Kjetill S, Linke, Dirk, Tørresen, Ole K, Star, Bastiaan, Mier, Pablo, Andrade-Navarro, Miguel A, Bateman, Alex, Jarnot, Patryk, Gruca, Aleksandra, Grynberg, Marcin, Kajava, Andrey V, Promponas, Vasilis J, Anisimova, Maria, Jakobsen, Kjetill S, and Linke, Dirk

Abstract

The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with 'ready-to-use' deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where misannotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others.

Published
2019

12. Quantitative Conformational Analysis of Functionally Important Electrostatic Interactions in the Intrinsically Disordered Region of Delta Subunit of Bacterial RNA Polymerase

Author

Kubáň, Vojtěch, primary, Srb, Pavel, additional, Štégnerová, Hana, additional, Padrta, Petr, additional, Zachrdla, Milan, additional, Jaseňáková, Zuzana, additional, Šanderová, Hana, additional, Vítovská, Dragana, additional, Krásný, Libor, additional, Koval’, Tomáš, additional, Dohnálek, Jan, additional, Ziemska-Legiecka, Joanna, additional, Grynberg, Marcin, additional, Jarnot, Patryk, additional, Gruca, Aleksandra, additional, Jensen, Malene Ringkjøbing, additional, Blackledge, Martin, additional, and Žídek, Lukáš, additional

Published
2019
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13. Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases.

Author

Tørresen OK, Star B, Mier P, Andrade-Navarro MA, Bateman A, Jarnot P, Gruca A, Grynberg M, Kajava AV, Promponas VJ, Anisimova M, Jakobsen KS, and Linke D

Subjects
Animals, Gadus morhua genetics, Sequence Analysis, DNA, DNA genetics, Databases, Nucleic Acid, Databases, Protein, Scientific Experimental Error, Tandem Repeat Sequences genetics
Abstract

The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with 'ready-to-use' deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where mis-annotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Published
2019
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