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Publications (10 of 10) Show all publications
Gorreja, F., Rush, S., Kasper, D., Brummer, R. J., Meng, D. & Walker, W. A. (2018). Beneficial bacteria that affect Toll-like receptors in the gut immune system: the case of PSA on Bacteroides fragilis and transcription profile of developmentally-regulated genes. In: : . Paper presented at Nobel Day, 10th Conference, School of Medical Sceinces, Örebro University, 10 December, 2018.
Open this publication in new window or tab >>Beneficial bacteria that affect Toll-like receptors in the gut immune system: the case of PSA on Bacteroides fragilis and transcription profile of developmentally-regulated genes
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2018 (English)Conference paper, Poster (with or without abstract) (Other academic)
National Category
Medical and Health Sciences Immunology
Identifiers
urn:nbn:se:oru:diva-70701 (URN)
Conference
Nobel Day, 10th Conference, School of Medical Sceinces, Örebro University, 10 December, 2018
Available from: 2018-12-11 Created: 2018-12-11 Last updated: 2018-12-17Bibliographically approved
Rush, S. & Repsilber, D. (2018). Capturing context-specific regulation in molecular interaction networks. BMC Bioinformatics, 19(1), Article ID 539.
Open this publication in new window or tab >>Capturing context-specific regulation in molecular interaction networks
2018 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 19, no 1, article id 539Article in journal (Refereed) Published
Abstract [en]

Background: Molecular profiles change in response to perturbations. These changes are coordinated into functional modules via regulatory interactions. The genes and their products within a functional module are expected to be differentially expressed in a manner coherent with their regulatory network. This perspective presents a promising approach to increase precision in detecting differential signals as well as for describing differential regulatory signals within the framework of a priori knowledge about the underlying network, and so from a mechanistic point of view.

Results: We present Coherent Network Expression (CoNE), an effective procedure for identifying differentially activated functional modules in molecular interaction networks. Differential gene expression is chosen as example, and differential signals coherent with the regulatory nature of the network are identified. We apply our procedure to systematically simulated data, comparing its performance to alternative methods. We then take the example case of a transcription regulatory network in the context of particle-induced pulmonary inflammation, recapitulating and proposing additional candidates to previously obtained results. CoNE is conveniently implemented in an R-package along with simulation utilities.

Conclusion: Combining coherent interactions with error control on differential gene expression results in uniformly greater specificity in inference than error control alone, ensuring that captured functional modules constitute real findings.

Place, publisher, year, edition, pages
BioMed Central, 2018
Keywords
Activated subnetwork, Coherent differential expression, Differential regulation, Error control, Functional module, Molecular network
National Category
Bioinformatics and Systems Biology
Identifiers
urn:nbn:se:oru:diva-65214 (URN)10.1186/s12859-018-2513-7 (DOI)000454209300003 ()30577761 (PubMedID)2-s2.0-85058920164 (Scopus ID)
Funder
Knowledge Foundation, 20110225
Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2019-01-11Bibliographically approved
Gorreja, F., Rangel, I., Rush, S., Wall, R., De Vos, W. M. & Brummer, R. J. (2018). Double-blind cross-over trial reveals human mucosal transcriptome responses to variants of LGG administration in vivo. In: Peter Konturek (Ed.), Targeting microbiota: 6th World congress on targeting microbiota towards clinical revolution. Paper presented at 6th World Congress on Targeting Microbiota, Porto, Portugal, October 28-30, 2018. Porto, Portugal: ISM, 5, Article ID 978-2-35609-010-2.
Open this publication in new window or tab >>Double-blind cross-over trial reveals human mucosal transcriptome responses to variants of LGG administration in vivo
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2018 (English)In: Targeting microbiota: 6th World congress on targeting microbiota towards clinical revolution / [ed] Peter Konturek, Porto, Portugal: ISM , 2018, Vol. 5, article id 978-2-35609-010-2Conference paper, Poster (with or without abstract) (Other academic)
Place, publisher, year, edition, pages
Porto, Portugal: ISM, 2018
Series
Archives of international society of microbiota, ISSN 978-2-35609-010-2
National Category
Medical and Health Sciences Genetics
Identifiers
urn:nbn:se:oru:diva-69884 (URN)
Conference
6th World Congress on Targeting Microbiota, Porto, Portugal, October 28-30, 2018
Available from: 2018-10-28 Created: 2018-10-28 Last updated: 2018-11-12Bibliographically approved
Gorreja, F., Rush, S., Marques, T. M., Repsilber, D., Baker, A., Wall, R. & Brummer, R. J. (2018). The impacts of probiotics and prebiotics on the gut mucosa and immune system through targeting inflammation and intestinal barrier function. In: : . Paper presented at Food and Inflammation - 2nd Conference of Food Science Sweden, Örebro, Sweden, 21 Nov., 2018.
Open this publication in new window or tab >>The impacts of probiotics and prebiotics on the gut mucosa and immune system through targeting inflammation and intestinal barrier function
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2018 (English)Conference paper, Oral presentation only (Other academic)
Keywords
Probiotics, Inflammation, Prebiotics, Immune system, Dietary
National Category
Medical and Health Sciences Microbiology
Research subject
Molecular Biology; Medicine; Microbiology
Identifiers
urn:nbn:se:oru:diva-70257 (URN)
Conference
Food and Inflammation - 2nd Conference of Food Science Sweden, Örebro, Sweden, 21 Nov., 2018
Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2019-04-24Bibliographically approved
Sommerfeld, M., Heo, G., Kim, P., Rush, S. & Marron, J. S. (2017). Bump hunting by topological data analysis. Stat, 6(1), 462-471
Open this publication in new window or tab >>Bump hunting by topological data analysis
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2017 (English)In: Stat, E-ISSN 2049-1573, Vol. 6, no 1, p. 462-471Article in journal (Refereed) Published
Abstract [en]

A topological data analysis approach is taken to the challenging problem of finding and validating the statistical significance of local modes in a data set. As with the SIgnificance of the ZERo (SiZer) approach to this problem, statistical inference is performed in a multi-scale way, that is, across bandwidths. The key contribution is a twoparameter approach to the persistent homology representation. For each kernel bandwidth, a sub-level set filtration of the resulting kernel density estimate is computed. Inference based on the resulting persistence diagram indicates statistical significance of modes. It is seen through a simulated example, and by analysis of the famous Hidalgo stamps data, that the new method has more statistical power for finding bumps than SiZer.

Place, publisher, year, edition, pages
John Wiley & Sons, 2017
Keywords
Bootstrap, kernel density estimation, mode hunting, persistent homology, SiZer
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:oru:diva-65213 (URN)10.1002/sta4.167 (DOI)000441301200019 ()2-s2.0-85051252789 (Scopus ID)
Note

Funding Agencies:

Studienstiftung des Deutschen Volkes  

Natural Sciences and Engineering Research Council of Canada  DG 293180 

McIntyre Memorial Fund  

US National Science Foundation  IIS-1633074 

Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2018-08-27Bibliographically approved
Kim, P., Pinder, S. & Rush, S. (2014). Fréchet analysis and the microbiome. Journal of Statistical Planning and Inference, 145, 37-41
Open this publication in new window or tab >>Fréchet analysis and the microbiome
2014 (English)In: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 145, p. 37-41Article in journal (Refereed) Published
Abstract [en]

The paper under discussion provides a detailed survey of the important developments in Fréchet analysis on manifolds or on stratified sample spaces. As it appears that data is now being realized over non-Euclidean spaces, such a paper is timely as such methods are called for in modern data analysis. In this discussion we explore this in the context of computational biology in general, and in particular for microbiome data which is gaining in popularity both in the scholarly and the popular presses. We will discuss the microbiome and metagenomics as well as outline how data is collected and strategies for data analysis. Finally we tie in how the microbiome data can be analyzed within the context of Fréchet analysis.

Place, publisher, year, edition, pages
Elsevier, 2014
Keywords
16S rRNA, Metagenomics, Microbiology, OTU, Persistent homology, Phylogenetic tree space, Phylotypes, Pyrosequencing, Unifrac metric, Wasserstein metric, Fréchet means
National Category
Probability Theory and Statistics Biological Sciences
Identifiers
urn:nbn:se:oru:diva-65208 (URN)10.1016/j.jspi.2013.08.005 (DOI)000327828200005 ()2-s2.0-84887607050 (Scopus ID)
Note

Funding Agencies:

NSERC 

CIHR-NSERC 

Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2018-03-13Bibliographically approved
Pereira, R. & Rush, S. (2013). Wielandt's theorem, spectral sets, and Banach algebras. Linear Algebra and its Applications, 439(4), 852-855
Open this publication in new window or tab >>Wielandt's theorem, spectral sets, and Banach algebras
2013 (English)In: Linear Algebra and its Applications, ISSN 0024-3795, E-ISSN 1873-1856, Vol. 439, no 4, p. 852-855Article in journal (Refereed) Published
Abstract [en]

Let A be a complex unital Banach algebra and let a,b∈A. We give regions of the complex plane which contain the spectrum of a+b or ab using von Neumann spectral set theory. These results are a direct generalization of a theorem of Wielandt on the eigenvalues of the sum of two normal matrices.

Place, publisher, year, edition, pages
Elsevier, 2013
Keywords
Banach algebras, Spectral sets, Spectral inclusion regions, Normal matrices, Von Neumann operators
National Category
Mathematics
Identifiers
urn:nbn:se:oru:diva-65205 (URN)10.1016/j.laa.2012.06.019 (DOI)000321084700007 ()2-s2.0-84879881534 (Scopus ID)
Note

Funding Agency:

National Science and Engineering Research Council of Canada

Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2018-05-29Bibliographically approved
Rush, S., Pinder, S., Costa, M. & Kim, P. (2012). A microbiology primer for pyrosequencing. Quantitative Bio-Science, 31(2), 53-81
Open this publication in new window or tab >>A microbiology primer for pyrosequencing
2012 (English)In: Quantitative Bio-Science, ISSN 2288-1344, Vol. 31, no 2, p. 53-81Article in journal (Refereed) Published
Abstract [en]

Metagenomic analysis is a very rich area for understanding the microbiology of organisms. Once the data has been assembled mathematical and statistical methods can be applied providing insights into biological properties that created the data in the first place. The foundations however, require some knowledge of microbiology which is not usually part of a mathematician’s nor a statistician’s training, and therefore, the data creation can itself be quite mysterious. In this paper we attempt to explain the microbiology to mathematicians and statisticians in a way that would hopefully provide insights into the data generating process. In particular our approach is specific to the open-source bioinformatics toolbox mothur. We will assume the reader has very little microbiology training but has some mathematical skills. It is the endeavor of this write-up to help bridge a needed gap.

Place, publisher, year, edition, pages
Daegu, Korea: Natural Science Institute, College of Natural Sciences, Keimyung University, 2012
Keywords
BLAST, Clustering, Multivariate analysis, Operational taxonomic unit, Reference library
National Category
Natural Sciences Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:oru:diva-65207 (URN)
Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2018-05-15Bibliographically approved
Rush, S., Lee, C., Mio, W. & Kim, P.The phylogenetic LASSO and the microbiome.
Open this publication in new window or tab >>The phylogenetic LASSO and the microbiome
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Scientific investigations that incorporate next generation sequencing involve analyses of high-dimensional data where the need to organize, collate and interpret the outcomes are pressingly important. Currently, data can be collected at the microbiome level leading to the possibility of personalized medicine whereby treatments can be tailored at this scale. In this paper, we lay down a statistical framework for this type of analysis with a view toward synthesis of products tailored to individual patients. Although the paper applies the technique to data for a particular infectious disease, the methodology is suciently rich to be expanded to other problems in medicine, especially those in which coincident `-omics' covariates and clinical responses are simultaneously captured.

Keywords
Bacteriology, Bioinformatics, Clostridium dicile Infection, Faecal Microbiota Transplantation, LASSO, Optimization, Oracle Properties, Phylogeny, Public Health, 16S rRNA
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:oru:diva-65209 (URN)
Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2018-03-16Bibliographically approved
Petrov, P., Rush, S., Zhai, Z., Lee, C. H., Kim, P. T. & Heo, G.Topological data analysis of Clostridioides difficile infection and fecal microbiota transplantation.
Open this publication in new window or tab >>Topological data analysis of Clostridioides difficile infection and fecal microbiota transplantation
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(English)Manuscript (preprint) (Other academic)
Keywords
Persistent homology, Persistence landscape, Discriminant analysis, Clostridioides difficile, Fecal Microbiota Transplantation; DNA sequences, 16S rRNA gene
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:oru:diva-65211 (URN)
Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2018-03-16Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-2437-1300

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