LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 104

Search options

  1. Book ; Online ; E-Book: Human genome informatics

    Lambert, Christophe G. / Baker, Darrol J. / Patrinos, George P.

    translating genes into health

    (Translational and applied genomics series)

    2018  

    Author's details edited by Christophe G. Lambert, Darrol J. Baker, George P. Patrinos
    Series title Translational and applied genomics series
    Language English
    Size 1 Online-Ressource (xvi, 298 Seiten), Illustrationen, Diagramme
    Publisher Academic Press, an imprint of Elsevier
    Publishing place London
    Publishing country Great Britain
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019800782
    ISBN 978-0-12-813431-3 ; 9780128094143 ; 0-12-813431-3 ; 0128094141
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    Kategorien

  2. Book ; Online: Positive Unlabeled Learning Selected Not At Random (PULSNAR)

    Kumar, Praveen / Lambert, Christophe G.

    class proportion estimation when the SCAR assumption does not hold

    2023  

    Abstract: Positive and Unlabeled (PU) learning is a type of semi-supervised binary classification where the machine learning algorithm differentiates between a set of positive instances (labeled) and a set of both positive and negative instances (unlabeled). PU ... ...

    Abstract Positive and Unlabeled (PU) learning is a type of semi-supervised binary classification where the machine learning algorithm differentiates between a set of positive instances (labeled) and a set of both positive and negative instances (unlabeled). PU learning has broad applications in settings where confirmed negatives are unavailable or difficult to obtain, and there is value in discovering positives among the unlabeled (e.g., viable drugs among untested compounds). Most PU learning algorithms make the selected completely at random (SCAR) assumption, namely that positives are selected independently of their features. However, in many real-world applications, such as healthcare, positives are not SCAR (e.g., severe cases are more likely to be diagnosed), leading to a poor estimate of the proportion, $\alpha$, of positives among unlabeled examples and poor model calibration, resulting in an uncertain decision threshold for selecting positives. PU learning algorithms can estimate $\alpha$ or the probability of an individual unlabeled instance being positive or both. We propose two PU learning algorithms to estimate $\alpha$, calculate calibrated probabilities for PU instances, and improve classification metrics: i) PULSCAR (positive unlabeled learning selected completely at random), and ii) PULSNAR (positive unlabeled learning selected not at random). PULSNAR uses a divide-and-conquer approach that creates and solves several SCAR-like sub-problems using PULSCAR. In our experiments, PULSNAR outperformed state-of-the-art approaches on both synthetic and real-world benchmark datasets.
    Keywords Computer Science - Machine Learning
    Subject code 006
    Publishing date 2023-03-14
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  3. Book ; Online: UNM Global Health COVID-19 Briefing Participants

    Lambert, Christophe G / Stoicu, Shawn

    HSC Covid 19 Briefings

    2020  

    Keywords COVID-19 ; Coronavirus ; Coronavirus disease ; Coronavirus pandemic ; SARS-CoV-2 ; Epidemic ; Public Health ; covid19
    Publishing date 2020-06-30T07:00:00Z
    Publisher UNM Digital Repository
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  4. Article ; Online: Ingestion of hemozoin by peripheral blood mononuclear cells alters temporal gene expression of ubiquitination processes.

    Anyona, Samuel B / Cheng, Qiuying / Raballah, Evans / Hurwitz, Ivy / Lambert, Christophe G / McMahon, Benjamin H / Ouma, Collins / Perkins, Douglas J

    Biochemistry and biophysics reports

    2022  Volume 29, Page(s) 101207

    Abstract: Plasmodium falciparum (Pf) ...

    Abstract Plasmodium falciparum (Pf)
    Language English
    Publishing date 2022-01-11
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2831046-9
    ISSN 2405-5808 ; 2405-5808
    ISSN (online) 2405-5808
    ISSN 2405-5808
    DOI 10.1016/j.bbrep.2022.101207
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  5. Article: LocalControl: An R Package for Comparative Safety and Effectiveness Research.

    Lauve, Nicolas R / Nelson, Stuart J / Young, S Stanley / Obenchain, Robert L / Lambert, Christophe G

    Journal of statistical software

    2020  Volume 96, Issue 4

    Abstract: ... ...

    Abstract The
    Language English
    Publishing date 2020-11-29
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2010240-9
    ISSN 1548-7660
    ISSN 1548-7660
    DOI 10.18637/jss.v096.i04
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  6. Article ; Online: Human NCR3 gene variants rs2736191 and rs11575837 alter longitudinal risk for development of pediatric malaria episodes and severe malarial anemia.

    Onyango, Clinton O / Cheng, Qiuying / Munde, Elly O / Raballah, Evans / Anyona, Samuel B / McMahon, Benjamin H / Lambert, Christophe G / Onyango, Patrick O / Schneider, Kristan A / Perkins, Douglas J / Ouma, Collins

    BMC genomics

    2023  Volume 24, Issue 1, Page(s) 542

    Abstract: Background: Plasmodium falciparum malaria is a leading cause of pediatric morbidity and mortality in holoendemic transmission areas. Severe malarial anemia [SMA, hemoglobin (Hb) < 5.0 g/dL in children] is the most common clinical manifestation of severe ...

    Abstract Background: Plasmodium falciparum malaria is a leading cause of pediatric morbidity and mortality in holoendemic transmission areas. Severe malarial anemia [SMA, hemoglobin (Hb) < 5.0 g/dL in children] is the most common clinical manifestation of severe malaria in such regions. Although innate immune response genes are known to influence the development of SMA, the role of natural killer (NK) cells in malaria pathogenesis remains largely undefined. As such, we examined the impact of genetic variation in the gene encoding a primary NK cell receptor, natural cytotoxicity-triggering receptor 3 (NCR3), on the occurrence of malaria and SMA episodes over time.
    Methods: Susceptibility to malaria, SMA, and all-cause mortality was determined in carriers of NCR3 genetic variants (i.e., rs2736191:C > G and rs11575837:C > T) and their haplotypes. The prospective observational study was conducted over a 36 mos. follow-up period in a cohort of children (n = 1,515, aged 1.9-40 mos.) residing in a holoendemic P. falciparum transmission region, Siaya, Kenya.
    Results: Poisson regression modeling, controlling for anemia-promoting covariates, revealed a significantly increased risk of malaria in carriers of the homozygous mutant allele genotype (TT) for rs11575837 after multiple test correction [Incidence rate ratio (IRR) = 1.540, 95% CI = 1.114-2.129, P = 0.009]. Increased risk of SMA was observed for rs2736191 in children who inherited the CG genotype (IRR = 1.269, 95% CI = 1.009-1.597, P = 0.041) and in the additive model (presence of 1 or 2 copies) (IRR = 1.198, 95% CI = 1.030-1.393, P = 0.019), but was not significant after multiple test correction. Modeling of the haplotypes revealed that the CC haplotype had a significant additive effect for protection against SMA (i.e., reduced risk for development of SMA) after multiple test correction (IRR = 0.823, 95% CI = 0.711-0.952, P = 0.009). Although increased susceptibility to SMA was present in carriers of the GC haplotype (IRR = 1.276, 95% CI = 1.030-1.581, P = 0.026) with an additive effect (IRR = 1.182, 95% CI = 1.018-1.372, P = 0.029), the results did not remain significant after multiple test correction. None of the NCR3 genotypes or haplotypes were associated with all-cause mortality.
    Conclusions: Variation in NCR3 alters susceptibility to malaria and SMA during the acquisition of naturally-acquired malarial immunity. These results highlight the importance of NK cells in the innate immune response to malaria.
    MeSH term(s) Humans ; Child ; Malaria ; Anemia/genetics ; Genotype ; Malaria, Falciparum/genetics ; Alleles ; Natural Cytotoxicity Triggering Receptor 3
    Chemical Substances NCR3 protein, human ; Natural Cytotoxicity Triggering Receptor 3
    Language English
    Publishing date 2023-09-13
    Publishing country England
    Document type Observational Study ; Journal Article
    ZDB-ID 2041499-7
    ISSN 1471-2164 ; 1471-2164
    ISSN (online) 1471-2164
    ISSN 1471-2164
    DOI 10.1186/s12864-023-09565-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  7. Article ; Online: Search for compound heterozygous effects in exome sequence of unrelated subjects

    Christensen G / Lambert Christophe G

    BMC Proceedings , Vol 5, Iss Suppl 9, p S

    2011  Volume 95

    Abstract: Abstract To enable the assessment of compound heterozygosity, we propose a simple approach for incorporating genotype phase in a rare variant collapsing procedure for the analysis of DNA sequence data. When multiple variants are identified within a gene, ...

    Abstract Abstract To enable the assessment of compound heterozygosity, we propose a simple approach for incorporating genotype phase in a rare variant collapsing procedure for the analysis of DNA sequence data. When multiple variants are identified within a gene, knowing the phase of each variant may provide additional statistical power to detect associations with phenotypes that follow a recessive or additive inheritance pattern. We begin by phasing all marker data; then, we collapse nonsynonymous single-nucleotide polymorphisms within genes on each phased haplotype, resulting in a single diploid genotype for each gene, which represents whether one or both haplotypes carry a nonsynonymous variant allele. A recessive or additive association test can then be used to assess the relationship between the collapsed genotype and the phenotype of interest. We apply this approach to the unrelated individuals data from Genetic Analysis Workshop 17 and compare the results of the additive test with a dominant test in which phase is not informative. Analysis of the first phenotype replicate shows that the FLT1 gene is significantly associated with both Q1 and the binary affection status phenotype. This association was detected by both the additive and dominant tests, although the additive phase-informed test resulted in a smaller p -value. No false-positive results were detected in the first phenotype replicate. Analysis of the average values of all phenotype replicates correctly identified five other genes important to the simulation, but with an increase in false-positive rates. The accuracy of our method is contingent on correct phase determination.
    Keywords Biology (General) ; QH301-705.5 ; Science ; Q ; DOAJ:Biology ; DOAJ:Biology and Life Sciences ; Medicine (General) ; R5-920 ; Medicine ; R ; DOAJ:Medicine (General) ; DOAJ:Health Sciences
    Subject code 501
    Language English
    Publishing date 2011-11-01T00:00:00Z
    Publisher BioMed Central
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  8. Article: Bipolar disorder and diabetes mellitus: evidence for disease-modifying effects and treatment implications.

    Charles, Ellen F / Lambert, Christophe G / Kerner, Berit

    International journal of bipolar disorders

    2016  Volume 4, Issue 1, Page(s) 13

    Abstract: Background: Bipolar disorder refers to a group of chronic psychiatric disorders of mood and energy levels. While dramatic psychiatric symptoms dominate the acute phase of the diseases, the chronic course is often determined by an increasing burden of co- ...

    Abstract Background: Bipolar disorder refers to a group of chronic psychiatric disorders of mood and energy levels. While dramatic psychiatric symptoms dominate the acute phase of the diseases, the chronic course is often determined by an increasing burden of co-occurring medical conditions. High rates of diabetes mellitus in patients with bipolar disorder are particularly striking, yet unexplained. Treatment and lifestyle factors could play a significant role, and some studies also suggest shared pathophysiology and risk factors.
    Objective: In this systematic literature review, we explored data around the relationship between bipolar disorder and diabetes mellitus in recently published population-based cohort studies with special focus on the elderly.
    Methods: A systematic search in the PubMed database for the combined terms "bipolar disorder" AND "elderly" AND "diabetes" in papers published between January 2009 and December 2015 revealed 117 publications; 7 studies were large cohort studies, and therefore, were included in our review.
    Results: We found that age- and gender- adjusted risk for diabetes mellitus was increased in patients with bipolar disorder and vice versa (odds ratio range between 1.7 and 3.2).
    Discussion: Our results in large population-based cohort studies are consistent with the results of smaller studies and chart reviews. Even though it is likely that heterogeneous risk factors may play a role in diabetes mellitus and in bipolar disorder, growing evidence from cell culture experiments and animal studies suggests shared disease mechanisms. Furthermore, disease-modifying effects of bipolar disorder and diabetes mellitus on each other appear to be substantial, impacting both treatment response and outcomes.
    Conclusions: The risk of diabetes mellitus in patients with bipolar disorder is increased. Our findings add to the growing literature on this topic. Increasing evidence for shared disease mechanisms suggests new disease models that could explain the results of our study. A better understanding of the complex relationship between bipolar disorder and diabetes mellitus could lead to novel therapeutic approaches and improved outcomes.
    Language English
    Publishing date 2016-07-07
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 2732954-9
    ISSN 2194-7511
    ISSN 2194-7511
    DOI 10.1186/s40345-016-0054-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  9. Article ; Online: Imputation and characterization of uncoded self-harm in major mental illness using machine learning.

    Kumar, Praveen / Nestsiarovich, Anastasiya / Nelson, Stuart J / Kerner, Berit / Perkins, Douglas J / Lambert, Christophe G

    Journal of the American Medical Informatics Association : JAMIA

    2019  Volume 27, Issue 1, Page(s) 136–146

    Abstract: Objective: We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias.: Materials and methods: The IBM ... ...

    Abstract Objective: We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias.
    Materials and methods: The IBM MarketScan database (2003-2016) was used to analyze visit-level self-harm in 10 120 030 patients with ≥2 MMI codes. Five machine learning (ML) classifiers were tested on a balanced data subset, with XGBoost selected for the full dataset. Classification performance was validated via random data mislabeling and comparison with a clinician-derived "gold standard." The incidence of coded and imputed self-harm was characterized by year, patient age, sex, U.S. state, and MMI diagnosis.
    Results: Imputation identified 1 592 703 self-harm events vs 83 113 coded events, with areas under the curve >0.99 for the balanced and full datasets, and 83.5% agreement with the gold standard. The overall coded and imputed self-harm incidence were 0.28% and 5.34%, respectively, varied considerably by age and sex, and was highest in individuals with multiple MMI diagnoses. Self-harm undercoding was higher in male than in female individuals and increased with age. Substance abuse, injuries, poisoning, asphyxiation, brain disorders, harmful thoughts, and psychotherapy were the main features used by ML to classify visits.
    Discussion: Only 1 of 19 self-harm events was coded for individuals with MMI. ML demonstrated excellent performance in recovering self-harm visits. Male individuals and seniors with MMI are particularly vulnerable to self-harm undercoding and may be at risk of not getting appropriate psychiatric care.
    Conclusions: ML can effectively recover unrecorded self-harm in claims data and inform psychiatric epidemiological and observational studies.
    MeSH term(s) Adult ; Algorithms ; Classification/methods ; Clinical Coding/methods ; Datasets as Topic ; Electronic Health Records ; Female ; Humans ; Incidence ; Machine Learning ; Male ; Mental Disorders/classification ; Mental Disorders/psychology ; Self-Injurious Behavior/classification ; Self-Injurious Behavior/diagnosis ; Self-Injurious Behavior/epidemiology ; Suicidal Ideation
    Language English
    Publishing date 2019-10-24
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1205156-1
    ISSN 1527-974X ; 1067-5027
    ISSN (online) 1527-974X
    ISSN 1067-5027
    DOI 10.1093/jamia/ocz173
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  10. Article ; Online: Learning from our GWAS mistakes: from experimental design to scientific method.

    Lambert, Christophe G / Black, Laura J

    Biostatistics (Oxford, England)

    2012  Volume 13, Issue 2, Page(s) 195–203

    Abstract: Many public and private genome-wide association studies that we have analyzed include flaws in design, with avoidable confounding appearing as a norm rather than the exception. Rather than recognizing flawed research design and addressing that, a ... ...

    Abstract Many public and private genome-wide association studies that we have analyzed include flaws in design, with avoidable confounding appearing as a norm rather than the exception. Rather than recognizing flawed research design and addressing that, a category of quality-control statistical methods has arisen to treat only the symptoms. Reflecting more deeply, we examine elements of current genomic research in light of the traditional scientific method and find that hypotheses are often detached from data collection, experimental design, and causal theories. Association studies independent of causal theories, along with multiple testing errors, too often drive health care and public policy decisions. In an era of large-scale biological research, we ask questions about the role of statistical analyses in advancing coherent theories of diseases and their mechanisms. We advocate for reinterpretation of the scientific method in the context of large-scale data analysis opportunities and for renewed appreciation of falsifiable hypotheses, so that we can learn more from our best mistakes.
    MeSH term(s) Biostatistics ; Data Collection ; Data Interpretation, Statistical ; Genome-Wide Association Study/methods ; Genome-Wide Association Study/statistics & numerical data ; Humans ; Models, Genetic
    Language English
    Publishing date 2012-01-27
    Publishing country England
    Document type Editorial
    ZDB-ID 2031500-4
    ISSN 1468-4357 ; 1465-4644
    ISSN (online) 1468-4357
    ISSN 1465-4644
    DOI 10.1093/biostatistics/kxr055
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

To top