The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Erich Bornberg-bauer - One of the best experts on this subject based on the ideXlab platform.
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Dogma: a web server for proteome and transcriptome quality assessment.
Nucleic acids research, 2019Co-Authors: Carsten Kemena, Elias Dohmen, Erich Bornberg-bauerAbstract:Even in the era of next generation sequencing, in which bioinformatics tools abound, annotating transcriptomes and proteomes remains a challenge. This can have major implications for the reliability of studies based on these datasets. Therefore, quality assessment represents a crucial step prior to downstream analyses on novel transcriptomes and proteomes. Dogma allows such a quality assessment to be carried out. The data of interest are evaluated based on a comparison with a core set of conserved protein domains and domain arrangements. Depending on the studied species, Dogma offers precomputed core sets for different phylogenetic clades. We now developed a web server for the Dogma software, offering a user-friendly, simple to use interface. Additionally, the server provides a graphical representation of the analysis results and their placement in comparison to publicly available data. The server is freely available under https://domainworld-services.uni-muenster.de/Dogma/. Additionally, for large scale analyses the software can be downloaded free of charge from https://domainworld.uni-muenster.de.
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Dogma: domain-based transcriptome and proteome quality assessment.
Bioinformatics (Oxford England), 2016Co-Authors: Elias Dohmen, Lukas P.m. Kremer, Erich Bornberg-bauer, Carsten KemenaAbstract:Motivation: Genome studies have become cheaper and easier than ever before, due to the decreased costs of high-throughput sequencing and the free availability of analysis software. However, the quality of genome or transcriptome assemblies can vary a lot. Therefore, quality assessment of assemblies and annotations are crucial aspects of genome analysis pipelines. Results: We developed Dogma, a program for fast and easy quality assessment of transcriptome and proteome data based on conserved protein domains. Dogma measures the completeness of a given transcriptome or proteome and provides information about domain content for further analysis. Dogma provides a very fast way to do quality assessment within seconds. Availability and Implementation: Dogma is implemented in Python and published under GNU GPL v.3 license. The source code is available on https://ebbgit.uni-muenster.de/domainWorld/Dogma/ . Contacts: e.dohmen@wwu.de or c.kemena@wwu.de Supplementary information: Supplementary data are available at Bioinformatics online.
Carsten Kemena - One of the best experts on this subject based on the ideXlab platform.
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Dogma: a web server for proteome and transcriptome quality assessment.
Nucleic acids research, 2019Co-Authors: Carsten Kemena, Elias Dohmen, Erich Bornberg-bauerAbstract:Even in the era of next generation sequencing, in which bioinformatics tools abound, annotating transcriptomes and proteomes remains a challenge. This can have major implications for the reliability of studies based on these datasets. Therefore, quality assessment represents a crucial step prior to downstream analyses on novel transcriptomes and proteomes. Dogma allows such a quality assessment to be carried out. The data of interest are evaluated based on a comparison with a core set of conserved protein domains and domain arrangements. Depending on the studied species, Dogma offers precomputed core sets for different phylogenetic clades. We now developed a web server for the Dogma software, offering a user-friendly, simple to use interface. Additionally, the server provides a graphical representation of the analysis results and their placement in comparison to publicly available data. The server is freely available under https://domainworld-services.uni-muenster.de/Dogma/. Additionally, for large scale analyses the software can be downloaded free of charge from https://domainworld.uni-muenster.de.
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Dogma: domain-based transcriptome and proteome quality assessment.
Bioinformatics (Oxford England), 2016Co-Authors: Elias Dohmen, Lukas P.m. Kremer, Erich Bornberg-bauer, Carsten KemenaAbstract:Motivation: Genome studies have become cheaper and easier than ever before, due to the decreased costs of high-throughput sequencing and the free availability of analysis software. However, the quality of genome or transcriptome assemblies can vary a lot. Therefore, quality assessment of assemblies and annotations are crucial aspects of genome analysis pipelines. Results: We developed Dogma, a program for fast and easy quality assessment of transcriptome and proteome data based on conserved protein domains. Dogma measures the completeness of a given transcriptome or proteome and provides information about domain content for further analysis. Dogma provides a very fast way to do quality assessment within seconds. Availability and Implementation: Dogma is implemented in Python and published under GNU GPL v.3 license. The source code is available on https://ebbgit.uni-muenster.de/domainWorld/Dogma/ . Contacts: e.dohmen@wwu.de or c.kemena@wwu.de Supplementary information: Supplementary data are available at Bioinformatics online.
Daniel T Levin - One of the best experts on this subject based on the ideXlab platform.
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two Dogmas of conceptual empiricism implications for hybrid models of the structure of knowledge
Cognition, 1998Co-Authors: Frank C Keil, Carter W Smith, Daniel J Simons, Daniel T LevinAbstract:Concepts seem to consist of both an associative component based on tabulations of feature typicality and similarity judgments and an explanatory component based on rules and causal principles. However, there is much controversy about how each component functions in concept acquisition and use. Here we consider two assumptions, or Dogmas, that embody this controversy and underlie much of the current cognitive science research on concepts. Dogma 1: Novel information is first processed via similarity judgments and only later is influenced by explanatory components. Dogma 2: Children initially have only a similarity-based component for learning concepts; the explanatory component develops on the foundation of this earlier component. We present both empirical and theoretical arguments that these Dogmas are unfounded, particularly with respect to real world concepts; we contend that the Dogmas arise from a particular species of empiricism that inhibits progress in the study of conceptual structure; and finally, we advocate the retention of a hybrid model of the structure of knowledge despite our rejection of these Dogmas.
Elias Dohmen - One of the best experts on this subject based on the ideXlab platform.
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Dogma: a web server for proteome and transcriptome quality assessment.
Nucleic acids research, 2019Co-Authors: Carsten Kemena, Elias Dohmen, Erich Bornberg-bauerAbstract:Even in the era of next generation sequencing, in which bioinformatics tools abound, annotating transcriptomes and proteomes remains a challenge. This can have major implications for the reliability of studies based on these datasets. Therefore, quality assessment represents a crucial step prior to downstream analyses on novel transcriptomes and proteomes. Dogma allows such a quality assessment to be carried out. The data of interest are evaluated based on a comparison with a core set of conserved protein domains and domain arrangements. Depending on the studied species, Dogma offers precomputed core sets for different phylogenetic clades. We now developed a web server for the Dogma software, offering a user-friendly, simple to use interface. Additionally, the server provides a graphical representation of the analysis results and their placement in comparison to publicly available data. The server is freely available under https://domainworld-services.uni-muenster.de/Dogma/. Additionally, for large scale analyses the software can be downloaded free of charge from https://domainworld.uni-muenster.de.
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Dogma: domain-based transcriptome and proteome quality assessment.
Bioinformatics (Oxford England), 2016Co-Authors: Elias Dohmen, Lukas P.m. Kremer, Erich Bornberg-bauer, Carsten KemenaAbstract:Motivation: Genome studies have become cheaper and easier than ever before, due to the decreased costs of high-throughput sequencing and the free availability of analysis software. However, the quality of genome or transcriptome assemblies can vary a lot. Therefore, quality assessment of assemblies and annotations are crucial aspects of genome analysis pipelines. Results: We developed Dogma, a program for fast and easy quality assessment of transcriptome and proteome data based on conserved protein domains. Dogma measures the completeness of a given transcriptome or proteome and provides information about domain content for further analysis. Dogma provides a very fast way to do quality assessment within seconds. Availability and Implementation: Dogma is implemented in Python and published under GNU GPL v.3 license. The source code is available on https://ebbgit.uni-muenster.de/domainWorld/Dogma/ . Contacts: e.dohmen@wwu.de or c.kemena@wwu.de Supplementary information: Supplementary data are available at Bioinformatics online.
Frank C Keil - One of the best experts on this subject based on the ideXlab platform.
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two Dogmas of conceptual empiricism implications for hybrid models of the structure of knowledge
Cognition, 1998Co-Authors: Frank C Keil, Carter W Smith, Daniel J Simons, Daniel T LevinAbstract:Concepts seem to consist of both an associative component based on tabulations of feature typicality and similarity judgments and an explanatory component based on rules and causal principles. However, there is much controversy about how each component functions in concept acquisition and use. Here we consider two assumptions, or Dogmas, that embody this controversy and underlie much of the current cognitive science research on concepts. Dogma 1: Novel information is first processed via similarity judgments and only later is influenced by explanatory components. Dogma 2: Children initially have only a similarity-based component for learning concepts; the explanatory component develops on the foundation of this earlier component. We present both empirical and theoretical arguments that these Dogmas are unfounded, particularly with respect to real world concepts; we contend that the Dogmas arise from a particular species of empiricism that inhibits progress in the study of conceptual structure; and finally, we advocate the retention of a hybrid model of the structure of knowledge despite our rejection of these Dogmas.