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1.
Hum Reprod ; 37(7): 1375-1378, 2022 06 30.
Artigo em Inglês | MEDLINE | ID: mdl-35604365

RESUMO

Recent advances in developing polygenic scores have made it possible to screen embryos for common, complex conditions and traits. Polygenic embryo screening (PES) is currently offered commercially, and though there has been much recent media and academic coverage, reproductive specialists' points of view have not yet been prominent in these discussions. We convened a roundtable of multidisciplinary experts, including reproductive specialists to discuss PES and its implications. In this Opinion, we describe four clinically relevant issues associated with the use of PES that have not yet been discussed in the literature and warrant consideration.


Assuntos
Programas de Rastreamento , Herança Multifatorial , Atenção , Embrião de Mamíferos , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Fenótipo
2.
Bioinformatics ; 21(10): 2301-8, 2005 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-15722375

RESUMO

SUMMARY: We introduce a novel unsupervised approach for the organization and visualization of multidimensional data. At the heart of the method is a presentation of the full pairwise distance matrix of the data points, viewed in pseudocolor. The ordering of points is iteratively permuted in search of a linear ordering, which can be used to study embedded shapes. Several examples indicate how the shapes of certain structures in the data (elongated, circular and compact) manifest themselves visually in our permuted distance matrix. It is important to identify the elongated objects since they are often associated with a set of hidden variables, underlying continuous variation in the data. The problem of determining an optimal linear ordering is shown to be NP-Complete, and therefore an iterative search algorithm with O(n3) step-complexity is suggested. By using sorting points into neighborhoods, i.e. SPIN to analyze colon cancer expression data we were able to address the serious problem of sample heterogeneity, which hinders identification of metastasis related genes in our data. Our methodology brings to light the continuous variation of heterogeneity--starting with homogeneous tumor samples and gradually increasing the amount of another tissue. Ordering the samples according to their degree of contamination by unrelated tissue allows the separation of genes associated with irrelevant contamination from those related to cancer progression. AVAILABILITY: Software package will be available for academic users upon request.


Assuntos
Algoritmos , Biomarcadores Tumorais/metabolismo , Neoplasias do Colo/metabolismo , Perfilação da Expressão Gênica/métodos , Armazenamento e Recuperação da Informação/métodos , Proteínas de Neoplasias/metabolismo , Interface Usuário-Computador , Biomarcadores Tumorais/classificação , Análise por Conglomerados , Neoplasias do Colo/diagnóstico , Neoplasias do Colo/genética , Gráficos por Computador , Simulação por Computador , Interpretação Estatística de Dados , Diagnóstico por Computador/métodos , Humanos , Modelos Biológicos , Proteínas de Neoplasias/classificação , Reconhecimento Automatizado de Padrão/métodos , Software
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