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Article ; Online: KELVIN: a software package for rigorous measurement of statistical evidence in human genetics.

Vieland, Veronica J / Huang, Yungui / Seok, Sang-Cheol / Burian, John / Catalyurek, Umit / O'Connell, Jeffrey / Segre, Alberto / Valentine-Cooper, William

Human heredity

2011 Volume 72, Issue 4, Page(s) 276–288

Abstract: This paper describes the software package KELVIN, which supports the PPL (posterior probability ... genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and ... while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software ...

Abstract	This paper describes the software package KELVIN, which supports the PPL (posterior probability of linkage) framework for the measurement of statistical evidence in human (or more generally, diploid) genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and multipoint linkage analysis, based on either sex-averaged or sex-specific genetic maps, with an option to allow for imprinting; trait-marker linkage disequilibrium (LD), or association analysis, in case-control data, trio data, and/or multiplex family data, with options for joint linkage and trait-marker LD or conditional LD given linkage; dichotomous trait, quantitative trait and quantitative trait threshold models; and certain types of gene-gene interactions and covariate effects. Features and data (pedigree) structures can be freely mixed and matched within analyses. The statistical framework is specifically tailored to accumulate evidence in a mathematically rigorous way across multiple data sets or data subsets while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software engineering to provide a powerful and robust platform for studying the genetics of complex disorders.
MeSH term(s)	Chromosome Mapping ; Epistasis, Genetic ; Genetic Linkage ; Genomic Imprinting ; Humans ; Linkage Disequilibrium ; Models, Genetic ; Models, Statistical ; Pedigree ; Quantitative Trait Loci ; Software
Language	English
Publishing date	2011-12-23
Publishing country	Switzerland
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2424-7
ISSN	1423-0062 ; 0001-5652
ISSN (online)	1423-0062
ISSN	0001-5652
DOI	10.1159/000330634
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Article: KELVIN: A Software Package for Rigorous Measurement of Statistical Evidence in Human Genetics

Vieland, Veronica J. / Huang, Yungui / Seok, Sang-Cheol / Burian, John / Catalyurek, Umit / O’Connell, Jeffrey / Segre, Alberto / Valentine-Cooper, William

Human Heredity

2011 Volume 72, Issue 4, Page(s) 276–288

Institution	Battelle Center for Mathematical Medicine, Research Institute at Nationwide Children’s Hospital, and Departments of Pediatrics and Statistics, and Biomedical Informatics, Ohio State University, Columbus, Ohio Department of Medicine, University of Maryland School of Medicine, Baltimore, Md., and Department of Computer Science, University of Iowa, Iowa City, Iowa, USA
Abstract	This paper describes the software package KELVIN, which supports the PPL (posterior probability of linkage) framework for the measurement of statistical evidence in human (or more generally, diploid) genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and multipoint linkage analysis, based on either sex-averaged or sex-specific genetic maps, with an option to allow for imprinting; trait-marker linkage disequilibrium (LD), or association analysis, in case-control data, trio data, and/or multiplex family data, with options for joint linkage and trait-marker LD or conditional LD given linkage; dichotomous trait, quantitative trait and quantitative trait threshold models; and certain types of gene-gene interactions and covariate effects. Features and data (pedigree) structures can be freely mixed and matched within analyses. The statistical framework is specifically tailored to accumulate evidence in a mathematically rigorous way across multiple data sets or data subsets while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software engineering to provide a powerful and robust platform for studying the genetics of complex disorders.
Keywords	Association ; Covariates ; Epistasis ; Imprinting ; Linkage ; Linkage disequilibrium ; Quantitative traits ; Software ; KELVIN ; Statistical evidence
Language	English
Publishing date	2011-12-23
Publisher	S. Karger AG
Publishing place	Basel, Switzerland
Document type	Article
ZDB-ID	2424-7
ISBN	978-3-8055-9941-2 ; 978-3-8055-9942-9 ; 3-8055-9941-2 ; 3-8055-9942-0
ISSN	1423-0062 ; 0001-5652
ISSN (online)	1423-0062
ISSN	0001-5652
DOI	10.1159/000330634
Database	Karger publisher's database

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Article ; Online: Clinical effectiveness of pharmacological and non-pharmacological treatments for the management of anxiety in community dwelling people living with dementia: A systematic review and meta-analysis.

Nimmons, Danielle / Aker, Narin / Burnand, Alice / Jordan, Kelvin P / Cooper, Claudia / Davies, Nathan / Manthorpe, Jill / Chew-Graham, Carolyn A / Kingstone, Tom / Petersen, Irene / Walters, Kate

Neuroscience and biobehavioral reviews

2023 Volume 157, Page(s) 105507

Abstract: People living with dementia commonly experience anxiety, which is often challenging to manage. We investigated the effectiveness of treatments for the management of anxiety in this population. We conducted a systematic review and meta-analysis of ... ...

Abstract	People living with dementia commonly experience anxiety, which is often challenging to manage. We investigated the effectiveness of treatments for the management of anxiety in this population. We conducted a systematic review and meta-analysis of randomised controlled trials, and searched EMBASE, CINAHL, MEDLINE and PsycInfo. We estimated standardised mean differences at follow-up between treatments relative to control groups and pooled these across studies using random-effects models where feasible. Thirty-one studies were identified. Meta-analysis demonstrated non-pharmacological interventions were effective in reducing anxiety in people living with dementia, compared to care as usual or active controls. Specifically, music therapy (SMD-1.92(CI:-2.58,-1.25)), muscular approaches (SMD-0.65(CI:-1.02,-0.28)) and stimulating cognitive and physical activities (SMD-0.31(CI:-0.53,-0.09)). Pharmacological interventions with evidence of potential effectiveness included Ginkgo biloba, probiotics, olanzapine, loxapine and citalopram compared to placebo, olanzapine compared to bromazepam and buspirone and risperidone compared to haloperidol. Meta-analyses were not performed for pharmacological interventions due to studies' heterogeneity. This has practice implications when promoting the use of more non-pharmacological interventions to help reduce anxiety among people living with dementia.
MeSH term(s)	Humans ; Independent Living ; Olanzapine ; Anxiety/therapy ; Treatment Outcome ; Dementia/complications ; Dementia/therapy
Chemical Substances	Olanzapine (N7U69T4SZR)
Language	English
Publishing date	2023-12-13
Publishing country	United States
Document type	Meta-Analysis ; Systematic Review ; Journal Article ; Review
ZDB-ID	282464-4
ISSN	1873-7528 ; 0149-7634
ISSN (online)	1873-7528
ISSN	0149-7634
DOI	10.1016/j.neubiorev.2023.105507
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Article ; Online: Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for the Effective Drug Design of SARS-CoV‑2 Target Antagonists and Inhibitors Using Machine Learning

Kelvin Cooper / Christopher Baddeley / Bernie French / Katherine Gibson / James Golden / Thiam Lee / Sadrach Pierre / Brent Weiss / Jason Yang

ACS Omega, Vol 6, Iss 7, Pp 4857-

2021 Volume 4877

Keywords	Chemistry ; QD1-999
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	American Chemical Society
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for the Effective Drug Design of SARS-CoV-2 Target Antagonists and Inhibitors Using Machine Learning.

Cooper, Kelvin / Baddeley, Christopher / French, Bernie / Gibson, Katherine / Golden, James / Lee, Thiam / Pierre, Sadrach / Weiss, Brent / Yang, Jason

ACS omega

2021 Volume 6, Issue 7, Page(s) 4857–4877

Abstract: A unique approach to bioactivity and chemical data curation coupled with random forest analyses has led to a series of target-specific and cross-validated predictive feature fingerprints (PFF) that have high predictability across multiple therapeutic ... ...

Abstract	A unique approach to bioactivity and chemical data curation coupled with random forest analyses has led to a series of target-specific and cross-validated predictive feature fingerprints (PFF) that have high predictability across multiple therapeutic targets and disease stages involved in the severe acute respiratory syndrome due to coronavirus 2 (SARS-CoV-2)-induced COVID-19 pandemic, which include plasma kallikrein, human immunodeficiency virus (HIV)-protease, nonstructural protein (NSP)5, NSP12, Janus kinase (JAK) family, and AT-1. The approach was highly accurate in determining the matched target for the different compound sets and suggests that the models could be used for virtual screening of target-specific compound libraries. The curation-modeling process was successfully applied to a SARS-CoV-2 phenotypic screen and could be used for predictive bioactivity estimation and prioritization for clinical trial selection; virtual screening of drug libraries for the repurposing of drug molecules; and analysis and direction of proprietary data sets.
Language	English
Publishing date	2021-02-05
Publishing country	United States
Document type	Journal Article
ISSN	2470-1343
ISSN (online)	2470-1343
DOI	10.1021/acsomega.0c05303
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Article ; Online: The prevalence of peripheral intravenous cannulae and pattern of use: A point prevalence in a private hospital setting.

Wong, Kelvin / Cooper, Alannah / Brown, Janie / Boyd, Leanne / Levinson, Michele

Journal of clinical nursing

2017

Abstract: Aims and objectives: to determine the prevalence and pattern of use of peripheral intravenous cannula (PIVC) in hospital wards.: Background: PIVC are commonly used in acute health care to directly access the bloodstream for the administration of ... ...

Abstract	Aims and objectives: to determine the prevalence and pattern of use of peripheral intravenous cannula (PIVC) in hospital wards. Background: PIVC are commonly used in acute health care to directly access the bloodstream for the administration of medications, intravenous fluids (IVF) and blood products. PIVC are associated with multiple adverse events including hospital acquired bloodstream infection, thrombophlebitis, and pain/discomfort. Administration of IVF is associated with impaired mobility and nocturia which may increase falls risk in the elderly. Design: observational, point prevalence study. Methods: Three private hospitals comprising a total of 1230 beds participated in the study. Nurses recorded the presence of a PIVC, duration of insertion, state of the dressing, and whether the PIVC was accessed in the previous 24 hours and for what purpose. Nurses were also asked if they would replace the PIVC should it fail. Results: Approximately one quarter of patients had a PIVC, the majority of which had been present for less than 24 hours. The major use of the PIVC was antibiotic administration. Administration of IVF occurred in the presence of normal oral fluid intake. Nurses would not replace one third of PIVC in the event of failure. A majority of patients were at increased falls risk and one third of these were receiving IVF. Conclusions: There is room for improvement in the utilisation of PIVC, particularly in removal and associated use of IVF. Alternative strategies for medication administration and timely switch to the oral route may reduce the risks associated with IVF. This article is protected by copyright. All rights reserved.
Language	English
Publishing date	2017-07-12
Publishing country	England
Document type	Journal Article
ZDB-ID	1159483-4
ISSN	1365-2702 ; 0962-1067 ; 1752-9816
ISSN (online)	1365-2702
ISSN	0962-1067 ; 1752-9816
DOI	10.1111/jocn.13961
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Book ; Online: Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for Effective Drug Design of SARS-CoV-2 Target Antagonists and Inhibitors Using Machine Learning

Kelvin Cooper / Christopher Baddeley / Bernie French / Katherine Gibson / James Golden / Thiam Lee / Sadrach Pierre / Brent Weiss / Jason Yang

2020

Abstract: A unique approach to bioactivity and chemical data curation coupled with Random forest analyses has led to a series of target-specific and cross-validated Predictive Feature Fingerprints (PFF) that have high predictability across multiple therapeutic ... ...

Abstract	A unique approach to bioactivity and chemical data curation coupled with Random forest analyses has led to a series of target-specific and cross-validated Predictive Feature Fingerprints (PFF) that have high predictability across multiple therapeutic targets and disease stages involved in the SARS-CoV-2 induced COVID-19 pandemic, which include plasma kallikrein, HIV protease, NSP5, NSP12, JAK family and AT-1. The approach was highly accurate in determining the matched target for the different compound sets and suggests that the models could be used for virtual screening of target specific compound libraries. The curation-modeling process was successfully applied to a SARS-CoV-2 phenotypic screen and could be used for predictive bioactivity estimation and prioritization for clinical trial selection, virtual screening of drug libraries for repurposing of drug molecules, and analysis and direction of proprietary datasets.
Keywords	Drug Discovery and Drug Delivery Systems ; SARS-CoV-2 ; COVID-19 ; Artificial Intelligence ; QSAR modeling approaches ; Random Forest ; Cluster Analysis ; Plasma Kallikrein ; HIV protease ; NSP5 ; NSP12 ; JAK 1 ; JAK 2 ; JAK 3 ; Angiotensin II receptors ; covid19
Publishing date	2020-10-29T06:02:04Z
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: DNA Methylation, Deamination, and Translesion Synthesis Combine to Generate Footprint Mutations in Cancer Driver Genes in B-Cell Derived Lymphomas and Other Cancers.

Rogozin, Igor B / Roche-Lima, Abiel / Tyryshkin, Kathrin / Carrasquillo-Carrión, Kelvin / Lada, Artem G / Poliakov, Lennard Y / Schwartz, Elena / Saura, Andreu / Yurchenko, Vyacheslav / Cooper, David N / Panchenko, Anna R / Pavlov, Youri I

Frontiers in genetics

2021 Volume 12, Page(s) 671866

Abstract: Cancer genomes harbor numerous genomic alterations and many cancers accumulate thousands of nucleotide sequence variations. A prominent fraction of these mutations arises as a consequence of the off-target activity of DNA/RNA editing cytosine deaminases ... ...

Abstract	Cancer genomes harbor numerous genomic alterations and many cancers accumulate thousands of nucleotide sequence variations. A prominent fraction of these mutations arises as a consequence of the off-target activity of DNA/RNA editing cytosine deaminases followed by the replication/repair of edited sites by DNA polymerases (pol), as deduced from the analysis of the DNA sequence context of mutations in different tumor tissues. We have used the weight matrix (sequence profile) approach to analyze mutagenesis due to Activation Induced Deaminase (AID) and two error-prone DNA polymerases. Control experiments using shuffled weight matrices and somatic mutations in immunoglobulin genes confirmed the power of this method. Analysis of somatic mutations in various cancers suggested that AID and DNA polymerases η and θ contribute to mutagenesis in contexts that almost universally correlate with the context of mutations in A:T and G:C sites during the affinity maturation of immunoglobulin genes. Previously, we demonstrated that AID contributes to mutagenesis in (de)methylated genomic DNA in various cancers. Our current analysis of methylation data from malignant lymphomas suggests that driver genes are subject to different (de)methylation processes than non-driver genes and, in addition to AID, the activity of pols η and θ contributes to the establishment of methylation-dependent mutation profiles. This may reflect the functional importance of interplay between mutagenesis in cancer and (de)methylation processes in different groups of genes. The resulting changes in CpG methylation levels and chromatin modifications are likely to cause changes in the expression levels of driver genes that may affect cancer initiation and/or progression.
Language	English
Publishing date	2021-05-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2021.671866
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: DNA Methylation, Deamination, and Translesion Synthesis Combine to Generate Footprint Mutations in Cancer Driver Genes in B-Cell Derived Lymphomas and Other Cancers

Igor B. Rogozin / Abiel Roche-Lima / Kathrin Tyryshkin / Kelvin Carrasquillo-Carrión / Artem G. Lada / Lennard Y. Poliakov / Elena Schwartz / Andreu Saura / Vyacheslav Yurchenko / David N. Cooper / Anna R. Panchenko / Youri I. Pavlov

Frontiers in Genetics, Vol

2021 Volume 12

Abstract	Cancer genomes harbor numerous genomic alterations and many cancers accumulate thousands of nucleotide sequence variations. A prominent fraction of these mutations arises as a consequence of the off-target activity of DNA/RNA editing cytosine deaminases followed by the replication/repair of edited sites by DNA polymerases (pol), as deduced from the analysis of the DNA sequence context of mutations in different tumor tissues. We have used the weight matrix (sequence profile) approach to analyze mutagenesis due to Activation Induced Deaminase (AID) and two error-prone DNA polymerases. Control experiments using shuffled weight matrices and somatic mutations in immunoglobulin genes confirmed the power of this method. Analysis of somatic mutations in various cancers suggested that AID and DNA polymerases η and θ contribute to mutagenesis in contexts that almost universally correlate with the context of mutations in A:T and G:C sites during the affinity maturation of immunoglobulin genes. Previously, we demonstrated that AID contributes to mutagenesis in (de)methylated genomic DNA in various cancers. Our current analysis of methylation data from malignant lymphomas suggests that driver genes are subject to different (de)methylation processes than non-driver genes and, in addition to AID, the activity of pols η and θ contributes to the establishment of methylation-dependent mutation profiles. This may reflect the functional importance of interplay between mutagenesis in cancer and (de)methylation processes in different groups of genes. The resulting changes in CpG methylation levels and chromatin modifications are likely to cause changes in the expression levels of driver genes that may affect cancer initiation and/or progression.
Keywords	tumor cells ; frequency matrices ; database ; computational biology ; somatic hypermutation ; immunoglobulin genes ; Genetics ; QH426-470
Subject code	570 ; 612
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for Effective Drug Design of SARS-CoV-2 Target Antagonists and Inhibitors Using Machine Learning

Cooper, Kelvin / Baddeley, Christopher / French, Bernie / Gibson, Katherine / Golden, James / Lee, Thiam / Pierre, Sadrach / Weiss, Brent / Yang, Jason

2020

Abstract: ... A unique approach to bioactivity and chemical data curation coupled with Random forest analyses has led to a series of target-specific and cross-validated Predictive Feature Fingerprints (PFF) that have high predictability across multiple therapeutic ... ...

Abstract	A unique approach to bioactivity and chemical data curation coupled with Random forest analyses has led to a series of target-specific and cross-validated Predictive Feature Fingerprints (PFF) that have high predictability across multiple therapeutic targets and disease stages involved in the SARS-CoV-2 induced COVID-19 pandemic, which include plasma kallikrein, HIV protease, NSP5, NSP12, JAK family and AT-1. The approach was highly accurate in determining the matched target for the different compound sets and suggests that the models could be used for virtual screening of target specific compound libraries. The curation-modeling process was successfully applied to a SARS-CoV-2 phenotypic screen and could be used for predictive bioactivity estimation and prioritization for clinical trial selection, virtual screening of drug libraries for repurposing of drug molecules, and analysis and direction of proprietary datasets.
Keywords	covid19
Publisher	American Chemical Society (ACS)
Publishing country	us
Document type	Book ; Online
DOI	10.26434/chemrxiv.13148111.v1
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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