The Experts below are selected from a list of 2547861 Experts worldwide ranked by ideXlab platform
Christophe Ravel - One of the best experts on this subject based on the ideXlab platform.
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Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Martine Piarroux, Farid Djenad, Carole Cassagne, Jean Donnadieu, Christophe RavelAbstract:Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania. However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani, L. guyanensis, and L. braziliensis complexes was observed, as previously reported for other techniques. The tested Application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers.
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Identification of Leishmania by MALDI-TOF mass spectrometry using a free Web-Based Application and a dedicated mass spectral library.
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Jean Luc Donnadieu, Martine Piarroux, Farid Djenad, Carole Cassagne, Christophe RavelAbstract:Human leishmaniasis are widely spread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and muco-cutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of MultiLocus Enzyme Electrophoresis. Moreover, these techniques are expensive, time-consuming and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for microorganism identification, including Leishmania However, no commercial reference mass spectral database is available. In this study, a reference mass spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass spectral identification, MSI), was constructed and tested. It includes mass spectral data for 33 different Leishmania species, including species that infect humans, animals and phlebotomine vectors. Four laboratories on two continents evaluated MSI performance using 268 samples of which 231 were Leishmania strains. All Leishmania strains, but one, were correctly identified at least at the complex level. A risk of species misidentification within the L. donovani, L. guyanensis and L. braziliensis complexes was observed, as already reported with other techniques. The tested Application was reliable, with identification results comparable to those obtained with reference methods, but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in the user's computers.
Laurence Lachaud - One of the best experts on this subject based on the ideXlab platform.
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Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Martine Piarroux, Farid Djenad, Carole Cassagne, Jean Donnadieu, Christophe RavelAbstract:Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania. However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani, L. guyanensis, and L. braziliensis complexes was observed, as previously reported for other techniques. The tested Application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers.
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Identification of Leishmania by MALDI-TOF mass spectrometry using a free Web-Based Application and a dedicated mass spectral library.
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Jean Luc Donnadieu, Martine Piarroux, Farid Djenad, Carole Cassagne, Christophe RavelAbstract:Human leishmaniasis are widely spread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and muco-cutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of MultiLocus Enzyme Electrophoresis. Moreover, these techniques are expensive, time-consuming and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for microorganism identification, including Leishmania However, no commercial reference mass spectral database is available. In this study, a reference mass spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass spectral identification, MSI), was constructed and tested. It includes mass spectral data for 33 different Leishmania species, including species that infect humans, animals and phlebotomine vectors. Four laboratories on two continents evaluated MSI performance using 268 samples of which 231 were Leishmania strains. All Leishmania strains, but one, were correctly identified at least at the complex level. A risk of species misidentification within the L. donovani, L. guyanensis and L. braziliensis complexes was observed, as already reported with other techniques. The tested Application was reliable, with identification results comparable to those obtained with reference methods, but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in the user's computers.
Norma Paniego - One of the best experts on this subject based on the ideXlab platform.
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ATGC transcriptomics: a Web-Based Application to integrate, explore and analyze de novo transcriptomic data
BMC Bioinformatics, 2017Co-Authors: Sergio Gonzalez, Bernardo Clavijo, Máximo Rivarola, Patricio Moreno, Paula Fernandez, Joaquín Dopazo, Norma PaniegoAbstract:Background In the last years, Applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. Results We developed a Web-Based Application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new Application simplifies data exploration, visualization, and integration for a better comprehension of the results. Conclusions ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net .
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ATGC transcriptomics: a Web-Based Application to integrate, explore and analyze de novo transcriptomic data.
BMC Bioinformatics, 2017Co-Authors: Sergio Gonzalez, Bernardo Clavijo, Máximo Rivarola, Patricio Moreno, Paula Fernandez, Joaquín Dopazo, Norma PaniegoAbstract:In the last years, Applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. We developed a Web-Based Application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new Application simplifies data exploration, visualization, and integration for a better comprehension of the results. ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net .
Patrick Lami - One of the best experts on this subject based on the ideXlab platform.
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Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Martine Piarroux, Farid Djenad, Carole Cassagne, Jean Donnadieu, Christophe RavelAbstract:Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania. However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani, L. guyanensis, and L. braziliensis complexes was observed, as previously reported for other techniques. The tested Application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers.
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Identification of Leishmania by MALDI-TOF mass spectrometry using a free Web-Based Application and a dedicated mass spectral library.
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Jean Luc Donnadieu, Martine Piarroux, Farid Djenad, Carole Cassagne, Christophe RavelAbstract:Human leishmaniasis are widely spread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and muco-cutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of MultiLocus Enzyme Electrophoresis. Moreover, these techniques are expensive, time-consuming and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for microorganism identification, including Leishmania However, no commercial reference mass spectral database is available. In this study, a reference mass spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass spectral identification, MSI), was constructed and tested. It includes mass spectral data for 33 different Leishmania species, including species that infect humans, animals and phlebotomine vectors. Four laboratories on two continents evaluated MSI performance using 268 samples of which 231 were Leishmania strains. All Leishmania strains, but one, were correctly identified at least at the complex level. A risk of species misidentification within the L. donovani, L. guyanensis and L. braziliensis complexes was observed, as already reported with other techniques. The tested Application was reliable, with identification results comparable to those obtained with reference methods, but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in the user's computers.
Cécile Nabet - One of the best experts on this subject based on the ideXlab platform.
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Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Martine Piarroux, Farid Djenad, Carole Cassagne, Jean Donnadieu, Christophe RavelAbstract:Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania. However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani, L. guyanensis, and L. braziliensis complexes was observed, as previously reported for other techniques. The tested Application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers.
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Identification of Leishmania by MALDI-TOF mass spectrometry using a free Web-Based Application and a dedicated mass spectral library.
Journal of Clinical Microbiology, 2017Co-Authors: Laurence Lachaud, Anna Fernández-arévalo, Anne Cécile Normand, Patrick Lami, Cécile Nabet, Jean Luc Donnadieu, Martine Piarroux, Farid Djenad, Carole Cassagne, Christophe RavelAbstract:Human leishmaniasis are widely spread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and muco-cutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of MultiLocus Enzyme Electrophoresis. Moreover, these techniques are expensive, time-consuming and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for microorganism identification, including Leishmania However, no commercial reference mass spectral database is available. In this study, a reference mass spectral library (MSL) for Leishmania isolates, accessible through a free Web-Based Application (mass spectral identification, MSI), was constructed and tested. It includes mass spectral data for 33 different Leishmania species, including species that infect humans, animals and phlebotomine vectors. Four laboratories on two continents evaluated MSI performance using 268 samples of which 231 were Leishmania strains. All Leishmania strains, but one, were correctly identified at least at the complex level. A risk of species misidentification within the L. donovani, L. guyanensis and L. braziliensis complexes was observed, as already reported with other techniques. The tested Application was reliable, with identification results comparable to those obtained with reference methods, but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in the user's computers.
