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  1. Article: Ultrasound Technology: Providing "More" for Research and Clinical Care in Low-Resource Settings.

    Conlon, Thomas W / Himebauch, Adam S / Stratta, Erin M / Srinivasan, Vijay

    Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

    2022  Volume 23, Issue 7, Page(s) 560–562

    MeSH term(s) Health Resources ; Humans ; Ultrasonography
    Language English
    Publishing date 2022-07-01
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 2052349-X
    ISSN 1947-3893 ; 1529-7535
    ISSN (online) 1947-3893
    ISSN 1529-7535
    DOI 10.1097/PCC.0000000000002984
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    Zs.A 5600: Show issues Location:
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    Zs.MO 472: Show issues

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  2. Article ; Online: parallelMCMCcombine: an R package for bayesian methods for big data and analytics.

    Miroshnikov, Alexey / Conlon, Erin M

    PloS one

    2014  Volume 9, Issue 9, Page(s) e108425

    Abstract: Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets ...

    Abstract Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets that are large only due to large sample sizes. These methods partition big data sets into subsets and perform independent Bayesian Markov chain Monte Carlo analyses on the subsets. The methods then combine the independent subset posterior samples to estimate a posterior density given the full data set. These approaches were shown to be effective for Bayesian models including logistic regression models, Gaussian mixture models and hierarchical models. Here, we introduce the R package parallelMCMCcombine which carries out four of these techniques for combining independent subset posterior samples. We illustrate each of the methods using a Bayesian logistic regression model for simulation data and a Bayesian Gamma model for real data; we also demonstrate features and capabilities of the R package. The package assumes the user has carried out the Bayesian analysis and has produced the independent subposterior samples outside of the package. The methods are primarily suited to models with unknown parameters of fixed dimension that exist in continuous parameter spaces. We envision this tool will allow researchers to explore the various methods for their specific applications and will assist future progress in this rapidly developing field.
    MeSH term(s) Bayes Theorem ; Data Interpretation, Statistical ; Markov Chains ; Models, Statistical ; Monte Carlo Method ; Software
    Language English
    Publishing date 2014-09-26
    Publishing country United States
    Document type Journal Article
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0108425
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  3. Article: A Bayesian mixture model for metaanalysis of microarray studies.

    Conlon, Erin M

    Functional & integrative genomics

    2008  Volume 8, Issue 1, Page(s) 43–53

    Abstract: The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs ... ...

    Abstract The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs control. A recent Bayesian metaanalysis model used a prior distribution for the mean log-expression ratios that was a mixture of two normal distributions. This model centered the prior distribution of differential expression at zero, and separated genes into two groups only: expressed and nonexpressed. Here, we introduce a Bayesian three-component truncated normal mixture prior model that more flexibly assigns prior distributions to the differentially expressed genes and produces three groups of genes: up and downregulated, and nonexpressed. We found in simulations of two and five studies that the three-component model outperformed the two-component model using three comparison measures. When analyzing biological data of Bacillus subtilis, we found that the three-component model discovered more genes and omitted fewer genes for the same levels of posterior probability of differential expression than the two-component model, and discovered more genes for fixed thresholds of Bayesian false discovery. We assumed that the data sets were produced from the same microarray platform and were prescaled.
    MeSH term(s) Bacillus subtilis/genetics ; Bayes Theorem ; Computer Simulation ; Genes, Bacterial ; Meta-Analysis as Topic ; Models, Statistical ; Oligonucleotide Array Sequence Analysis/methods
    Language English
    Publishing date 2008-02
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2014670-X
    ISSN 1438-7948 ; 1438-793X
    ISSN (online) 1438-7948
    ISSN 1438-793X
    DOI 10.1007/s10142-007-0058-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: parallelMCMCcombine

    Alexey Miroshnikov / Erin M Conlon

    PLoS ONE, Vol 9, Iss 9, p e

    an R package for bayesian methods for big data and analytics.

    2014  Volume 108425

    Abstract: Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets ...

    Abstract Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets that are large only due to large sample sizes. These methods partition big data sets into subsets and perform independent Bayesian Markov chain Monte Carlo analyses on the subsets. The methods then combine the independent subset posterior samples to estimate a posterior density given the full data set. These approaches were shown to be effective for Bayesian models including logistic regression models, Gaussian mixture models and hierarchical models. Here, we introduce the R package parallelMCMCcombine which carries out four of these techniques for combining independent subset posterior samples. We illustrate each of the methods using a Bayesian logistic regression model for simulation data and a Bayesian Gamma model for real data; we also demonstrate features and capabilities of the R package. The package assumes the user has carried out the Bayesian analysis and has produced the independent subposterior samples outside of the package. The methods are primarily suited to models with unknown parameters of fixed dimension that exist in continuous parameter spaces. We envision this tool will allow researchers to explore the various methods for their specific applications and will assist future progress in this rapidly developing field.
    Keywords Medicine ; R ; Science ; Q
    Subject code 310
    Language English
    Publishing date 2014-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article: A Bayesian mixture model for metaanalysis of microarray studies

    Conlon, Erin M

    Functional & integrative genomics. 2008 Feb., v. 8, no. 1

    2008  

    Abstract: The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs ... ...

    Abstract The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs control. A recent Bayesian metaanalysis model used a prior distribution for the mean log-expression ratios that was a mixture of two normal distributions. This model centered the prior distribution of differential expression at zero, and separated genes into two groups only: expressed and nonexpressed. Here, we introduce a Bayesian three-component truncated normal mixture prior model that more flexibly assigns prior distributions to the differentially expressed genes and produces three groups of genes: up and downregulated, and nonexpressed. We found in simulations of two and five studies that the three-component model outperformed the two-component model using three comparison measures. When analyzing biological data of Bacillus subtilis, we found that the three-component model discovered more genes and omitted fewer genes for the same levels of posterior probability of differential expression than the two-component model, and discovered more genes for fixed thresholds of Bayesian false discovery. We assumed that the data sets were produced from the same microarray platform and were prescaled.
    Keywords Bacillus subtilis ; data collection ; gene expression regulation ; genes ; microarray technology ; models ; statistical analysis
    Language English
    Dates of publication 2008-02
    Size p. 43-53.
    Publisher Springer-Verlag
    Publishing place Berlin/Heidelberg
    Document type Article
    ZDB-ID 2014670-X
    ISSN 1438-7948 ; 1438-793X
    ISSN (online) 1438-7948
    ISSN 1438-793X
    DOI 10.1007/s10142-007-0058-3
    Database NAL-Catalogue (AGRICOLA)

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  6. Article: Genome Sequence of

    Pold, Grace / Conlon, Erin M / Huntemann, Marcel / Pillay, Manoj / Mikhailova, Natalia / Stamatis, Dimitrios / Reddy, T B K / Daum, Chris / Shapiro, Nicole / Kyrpides, Nikos / Woyke, Tanja / DeAngelis, Kristen M

    Genome announcements

    2018  Volume 6, Issue 4

    Abstract: ... ...

    Abstract Verrucomicrobium
    Language English
    Publishing date 2018-01-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2704277-7
    ISSN 2169-8287
    ISSN 2169-8287
    DOI 10.1128/genomeA.01451-17
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  7. Article ; Online: 90

    Conlon, Kevin C / Sportes, Claude / Brechbiel, Martin W / Fowler, Daniel H / Gress, Ronald / Miljkovic, Milos D / Chen, Clara C / Whatley, Millie A / Bryant, Bonita R / Corcoran, Erin M / Kurdziel, Karen A / Pittaluga, Stefania / Paik, Chang H / Lee, Jae Ho / Fleisher, Thomas A / Carrasquillo, Jorge A / Waldmann, Thomas A

    Cancer biotherapy & radiopharmaceuticals

    2020  Volume 35, Issue 4, Page(s) 249–261

    Abstract: Background: ...

    Abstract Background:
    MeSH term(s) Antineoplastic Combined Chemotherapy Protocols/pharmacology ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use ; Carmustine/pharmacology ; Carmustine/therapeutic use ; Cytarabine/pharmacology ; Cytarabine/therapeutic use ; Daclizumab/pharmacology ; Daclizumab/therapeutic use ; Etoposide/pharmacology ; Etoposide/therapeutic use ; Female ; Hematopoietic Stem Cell Transplantation/methods ; Hodgkin Disease/drug therapy ; Humans ; Male ; Melphalan/pharmacology ; Melphalan/therapeutic use ; Transplantation, Autologous/methods
    Chemical Substances Cytarabine (04079A1RDZ) ; Etoposide (6PLQ3CP4P3) ; Daclizumab (CUJ2MVI71Y) ; Melphalan (Q41OR9510P) ; Carmustine (U68WG3173Y)
    Language English
    Publishing date 2020-04-09
    Publishing country United States
    Document type Case Reports ; Clinical Trial, Phase I ; Clinical Trial, Phase II ; Journal Article
    ZDB-ID 1315649-4
    ISSN 1557-8852 ; 1084-9785
    ISSN (online) 1557-8852
    ISSN 1084-9785
    DOI 10.1089/cbr.2019.3298
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 1896: Show issues Location:
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  8. Article ; Online: RNA-seq in the tetraploid Xenopus laevis enables genome-wide insight in a classic developmental biology model organism.

    Amin, Nirav M / Tandon, Panna / Osborne Nishimura, Erin / Conlon, Frank L

    Methods (San Diego, Calif.)

    2013  Volume 66, Issue 3, Page(s) 398–409

    Abstract: Advances in sequencing technology have significantly advanced the landscape of developmental biology research. The dissection of genetic networks in model and non-model organisms has been greatly enhanced with high-throughput sequencing technologies. RNA- ...

    Abstract Advances in sequencing technology have significantly advanced the landscape of developmental biology research. The dissection of genetic networks in model and non-model organisms has been greatly enhanced with high-throughput sequencing technologies. RNA-seq has revolutionized the ability to perform developmental biology research in organisms without a published genome sequence. Here, we describe a protocol for developmental biologists to perform RNA-seq on dissected tissue or whole embryos. We start with the isolation of RNA and generation of sequencing libraries. We further show how to interpret and analyze the large amount of sequencing data that is generated in RNA-seq. We explore the abilities to examine differential expression, gene duplication, transcript assembly, alternative splicing and SNP discovery. For the purposes of this article, we use Xenopus laevis as the model organism to discuss uses of RNA-seq in an organism without a fully annotated genome sequence.
    MeSH term(s) Animals ; Developmental Biology/methods ; Genome ; Models, Animal ; Sequence Analysis, RNA/methods ; Xenopus laevis/genetics ; Xenopus laevis/growth & development
    Language English
    Publishing date 2013-06-20
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 1066584-5
    ISSN 1095-9130 ; 1046-2023
    ISSN (online) 1095-9130
    ISSN 1046-2023
    DOI 10.1016/j.ymeth.2013.06.009
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    Zs.A 3239: Show issues Location:
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  9. Article ; Online: Formation of a TBX20-CASZ1 protein complex is protective against dilated cardiomyopathy and critical for cardiac homeostasis.

    Kennedy, Leslie / Kaltenbrun, Erin / Greco, Todd M / Temple, Brenda / Herring, Laura E / Cristea, Ileana M / Conlon, Frank L

    PLoS genetics

    2017  Volume 13, Issue 9, Page(s) e1007011

    Abstract: By the age of 40, one in five adults without symptoms of cardiovascular disease are at risk for developing congestive heart failure. Within this population, dilated cardiomyopathy (DCM) remains one of the leading causes of disease and death, with nearly ... ...

    Abstract By the age of 40, one in five adults without symptoms of cardiovascular disease are at risk for developing congestive heart failure. Within this population, dilated cardiomyopathy (DCM) remains one of the leading causes of disease and death, with nearly half of cases genetically determined. Though genetic and high throughput sequencing-based approaches have identified sporadic and inherited mutations in a multitude of genes implicated in cardiomyopathy, how combinations of asymptomatic mutations lead to cardiac failure remains a mystery. Since a number of studies have implicated mutations of the transcription factor TBX20 in congenital heart diseases, we investigated the underlying mechanisms, using an unbiased systems-based screen to identify novel, cardiac-specific binding partners. We demonstrated that TBX20 physically and genetically interacts with the essential transcription factor CASZ1. This interaction is required for survival, as mice heterozygous for both Tbx20 and Casz1 die post-natally as a result of DCM. A Tbx20 mutation associated with human familial DCM sterically interferes with the TBX20-CASZ1 interaction and provides a physical basis for how this human mutation disrupts normal cardiac function. Finally, we employed quantitative proteomic analyses to define the molecular pathways mis-regulated upon disruption of this novel complex. Collectively, our proteomic, biochemical, genetic, and structural studies suggest that the physical interaction between TBX20 and CASZ1 is required for cardiac homeostasis, and further, that reduction or loss of this critical interaction leads to DCM. This work provides strong evidence that DCM can be inherited through a digenic mechanism.
    MeSH term(s) Animals ; Cardiomyopathy, Dilated/genetics ; Cardiomyopathy, Dilated/physiopathology ; DNA-Binding Proteins/chemistry ; DNA-Binding Proteins/genetics ; DNA-Binding Proteins/metabolism ; Heart Failure/genetics ; Heart Failure/physiopathology ; Humans ; Mice ; Mutation ; Proteomics ; T-Box Domain Proteins/chemistry ; T-Box Domain Proteins/genetics ; T-Box Domain Proteins/metabolism ; Transcription Factors/chemistry ; Transcription Factors/genetics ; Transcription Factors/metabolism
    Chemical Substances CASZ1 protein, human ; DNA-Binding Proteins ; T-Box Domain Proteins ; TBX20 protein, human ; Transcription Factors
    Language English
    Publishing date 2017-09-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2186725-2
    ISSN 1553-7404 ; 1553-7390
    ISSN (online) 1553-7404
    ISSN 1553-7390
    DOI 10.1371/journal.pgen.1007011
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  10. Article ; Online: Correction

    Jeffrey L. Blanchard / Wei-Yun Wholey / Erin M. Conlon / Pablo J. Pomposiello

    PLoS ONE, Vol 7, Iss

    Rapid Changes in Gene Expression Dynamics in Response to Superoxide Reveal SoxRS-Dependent and Independent Transcriptional Networks.

    2012  Volume 11

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2012-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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