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1.
Nat Commun ; 10(1): 3275, 2019 07 22.
Artigo em Inglês | MEDLINE | ID: mdl-31332201

RESUMO

The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N- and O-linked glycans (N- and O-glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase.


Assuntos
Biologia Computacional/métodos , Glicômica/métodos , Glicoproteínas/metabolismo , Polissacarídeos/metabolismo , Animais , Biologia Computacional/normas , Bases de Dados Factuais/normas , Bases de Dados Factuais/estatística & dados numéricos , Humanos , Espectrometria de Massas/métodos , Padrões de Referência
2.
Nat Commun ; 10(1): 2969, 2019 07 05.
Artigo em Inglês | MEDLINE | ID: mdl-31278357

RESUMO

Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.


Assuntos
Análise Mutacional de DNA/normas , Leucemia Linfocítica Crônica de Células B/genética , Leucemia Mieloide Aguda/genética , Mieloma Múltiplo/genética , Proteína BRCA1/genética , Proteína BRCA2/genética , Biologia Computacional/métodos , Biologia Computacional/normas , Análise Mutacional de DNA/métodos , Conjuntos de Dados como Assunto , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Sequenciamento de Nucleotídeos em Larga Escala/normas , Humanos , Mutação , Guias de Prática Clínica como Assunto , Sequenciamento Completo do Genoma/métodos , Sequenciamento Completo do Genoma/normas
3.
Food Chem Toxicol ; 132: 110656, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31279045

RESUMO

Part of the allergenicity assessment of newly expressed proteins in genetically engineered food crops involves an assessment of potential cross-reactivity with known allergens. Bioinformatic approaches are used to evaluate the amino acid sequence identity or similarity between newly expressed proteins and the sequences of known allergens. To be useful, such approaches must be sensitive to detecting cross-reactive potential, but also capable of excluding low-risk sequences. One difficulty in comparing the effectiveness of different bioinformatic approaches has been the lack of a standardized validation and evaluation method. Here, we propose a standardized method for evaluating the sensitivity of different bioinformatic algorithms using a comprehensive database of known allergen sequences. We combine this with a previously described method for evaluating selectivity using sequences from a crop not known to commonly cause food allergy (e.g. maize) to compare the standard ">35% identity-criterion over sliding-window of ≥80 amino acids" bioinformatic approach with the previously described "one-to-one (1:1) FASTA" similarity approach using an E-value threshold of 1E-9. Results confirm the superiority of the 1:1 FASTA approach for selectively detecting cross-reactive allergens. The validation methods described here can be applied to other algorithms to select even better fit-for-purpose approaches for evaluating cross-reactive risk.


Assuntos
Alérgenos/química , Biologia Computacional/normas , Proteínas de Plantas/química , Algoritmos , Alérgenos/imunologia , Sequência de Aminoácidos , Reações Cruzadas/imunologia , Bases de Dados de Proteínas/estatística & dados numéricos , Proteínas de Plantas/imunologia , Zea mays/química
4.
Database (Oxford) ; 20192019 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-31210270

RESUMO

Metadata-the machine-readable descriptions of the data-are increasingly seen as crucial for describing the vast array of biomedical datasets that are currently being deposited in public repositories. While most public repositories have firm requirements that metadata must accompany submitted datasets, the quality of those metadata is generally very poor. A key problem is that the typical metadata acquisition process is onerous and time consuming, with little interactive guidance or assistance provided to users. Secondary problems include the lack of validation and sparse use of standardized terms or ontologies when authoring metadata. There is a pressing need for improvements to the metadata acquisition process that will help users to enter metadata quickly and accurately. In this paper, we outline a recommendation system for metadata that aims to address this challenge. Our approach uses association rule mining to uncover hidden associations among metadata values and to represent them in the form of association rules. These rules are then used to present users with real-time recommendations when authoring metadata. The novelties of our method are that it is able to combine analyses of metadata from multiple repositories when generating recommendations and can enhance those recommendations by aligning them with ontology terms. We implemented our approach as a service integrated into the CEDAR Workbench metadata authoring platform, and evaluated it using metadata from two public biomedical repositories: US-based National Center for Biotechnology Information BioSample and European Bioinformatics Institute BioSamples. The results show that our approach is able to use analyses of previously entered metadata coupled with ontology-based mappings to present users with accurate recommendations when authoring metadata.


Assuntos
Mineração de Dados/métodos , Mineração de Dados/normas , Bases de Dados Factuais/normas , Metadados , Biologia Computacional/normas
5.
Neuron ; 103(3): 395-411.e5, 2019 08 07.
Artigo em Inglês | MEDLINE | ID: mdl-31201122

RESUMO

Computational models are powerful tools for exploring the properties of complex biological systems. In neuroscience, data-driven models of neural circuits that span multiple scales are increasingly being used to understand brain function in health and disease. But their adoption and reuse has been limited by the specialist knowledge required to evaluate and use them. To address this, we have developed Open Source Brain, a platform for sharing, viewing, analyzing, and simulating standardized models from different brain regions and species. Model structure and parameters can be automatically visualized and their dynamical properties explored through browser-based simulations. Infrastructure and tools for collaborative interaction, development, and testing are also provided. We demonstrate how existing components can be reused by constructing new models of inhibition-stabilized cortical networks that match recent experimental results. These features of Open Source Brain improve the accessibility, transparency, and reproducibility of models and facilitate their reuse by the wider community.


Assuntos
Encéfalo/fisiologia , Biologia Computacional/normas , Simulação por Computador , Modelos Neurológicos , Neurônios/fisiologia , Encéfalo/citologia , Biologia Computacional/métodos , Humanos , Internet , Sistemas On-Line
6.
PLoS Comput Biol ; 15(6): e1006989, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31194733

RESUMO

The Iowa Gambling Task (IGT) is one of the most common paradigms used to assess decision-making and executive functioning in neurological and psychiatric disorders. Several reinforcement-learning (RL) models were recently proposed to refine the qualitative and quantitative inferences that can be made about these processes based on IGT data. Yet, these models do not account for the complex exploratory patterns which characterize participants' behavior in the task. Using a dataset of more than 500 subjects, we demonstrate the existence of sequential exploration in the IGT and we describe a new computational architecture disentangling exploitation, random exploration and sequential exploration in this large population of participants. The new Value plus Sequential Exploration (VSE) architecture provided a better fit than previous models. Parameter recovery, model recovery and simulation analyses confirmed the superiority of the VSE scheme. Furthermore, using the VSE model, we confirmed the existence of a significant reduction in directed exploration across lifespan in the IGT, as previously reported with other paradigms. Finally, we provide a user-friendly toolbox enabling researchers to easily and flexibly fit computational models on the IGT data, hence promoting reanalysis of the numerous datasets acquired in various populations of patients and contributing to the development of computational psychiatry.


Assuntos
Tomada de Decisões/fisiologia , Modelos Psicológicos , Testes Neuropsicológicos/normas , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Biologia Computacional/normas , Simulação por Computador , Bases de Dados Factuais , Feminino , Jogo de Azar , Humanos , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Adulto Jovem
7.
Genome Biol ; 20(1): 118, 2019 06 04.
Artigo em Inglês | MEDLINE | ID: mdl-31164141

RESUMO

BACKGROUND: In high-throughput studies, hundreds to millions of hypotheses are typically tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular and powerful tools for error rate control. While classic FDR methods use only p values as input, more modern FDR methods have been shown to increase power by incorporating complementary information as informative covariates to prioritize, weight, and group hypotheses. However, there is currently no consensus on how the modern methods compare to one another. We investigate the accuracy, applicability, and ease of use of two classic and six modern FDR-controlling methods by performing a systematic benchmark comparison using simulation studies as well as six case studies in computational biology. RESULTS: Methods that incorporate informative covariates are modestly more powerful than classic approaches, and do not underperform classic approaches, even when the covariate is completely uninformative. The majority of methods are successful at controlling the FDR, with the exception of two modern methods under certain settings. Furthermore, we find that the improvement of the modern FDR methods over the classic methods increases with the informativeness of the covariate, total number of hypothesis tests, and proportion of truly non-null hypotheses. CONCLUSIONS: Modern FDR methods that use an informative covariate provide advantages over classic FDR-controlling procedures, with the relative gain dependent on the application and informativeness of available covariates. We present our findings as a practical guide and provide recommendations to aid researchers in their choice of methods to correct for false discoveries.


Assuntos
Biologia Computacional/métodos , Biologia Computacional/normas , Simulação por Computador
8.
Nat Commun ; 10(1): 2674, 2019 06 17.
Artigo em Inglês | MEDLINE | ID: mdl-31209238

RESUMO

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Biologia Computacional/métodos , Neoplasias/tratamento farmacológico , Farmacogenética/métodos , Proteína ADAM17/antagonistas & inibidores , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Benchmarking , Biomarcadores Tumorais/genética , Linhagem Celular Tumoral , Biologia Computacional/normas , Conjuntos de Dados como Assunto , Antagonismo de Drogas , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Resistencia a Medicamentos Antineoplásicos/genética , Sinergismo Farmacológico , Genômica/métodos , Humanos , Terapia de Alvo Molecular/métodos , Mutação , Neoplasias/genética , Farmacogenética/normas , Fosfatidilinositol 3-Quinases/genética , Resultado do Tratamento
9.
Genome Biol ; 20(1): 125, 2019 06 20.
Artigo em Inglês | MEDLINE | ID: mdl-31221194

RESUMO

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.


Assuntos
Biologia Computacional/normas , Guias como Assunto , Benchmarking , Conjuntos de Dados como Assunto , Editoração , Projetos de Pesquisa , Software
10.
Methods Mol Biol ; 1977: 237-248, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30980332

RESUMO

Proteomics based on mass spectrometry produces complex data in large quantities. The need for flexible computational pipelines, in the context of big data, in proteomics and other areas of science, has prompted the development of computational platforms and libraries that facilitate data analysis and data processing. In this respect, Python appears to be one of the winners among programming languages in terms of popularity and development. This chapter shows how to perform basic tasks using Python and dedicated libraries in a Jupyter framework: from basic search result summarizations to the creation of MS1 chromatograms.


Assuntos
Biologia Computacional/métodos , Proteômica , Software , Biologia Computacional/normas , Bases de Dados de Proteínas , Proteômica/métodos , Proteômica/normas , Reprodutibilidade dos Testes
11.
Methods Mol Biol ; 1933: 245-255, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30945189

RESUMO

Long noncoding RNAs (lncRNAs) have been shown to play important roles in various organisms, including plant species. Several tools and pipelines have emerged for lncRNA identification, including reference-based transcriptome assembly pipelines and various coding potential calculating tools. In this protocol, we have integrated some of the most updated computational tools and described the procedures step-by-step for identifying lncRNAs from plant strand-specific RNA-sequencing datasets. We will start from clean RNA-sequencing reads, followed by reference-based transcriptome assembly, filtering of known genes, and lncRNA prediction. At the end point, users will obtain a set of predicted lncRNAs for downstream use.


Assuntos
Arabidopsis/genética , Biologia Computacional/normas , Genoma de Planta , Sequenciamento de Nucleotídeos em Larga Escala/métodos , RNA Longo não Codificante/genética , RNA de Plantas/genética , Análise de Sequência de RNA/normas , Biologia Computacional/métodos , Regulação da Expressão Gênica de Plantas , Padrões de Referência , Análise de Sequência de RNA/métodos , Transcriptoma
12.
Methods Mol Biol ; 1970: 291-314, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30963499

RESUMO

MicroRNAs and their Argonaute protein partners constitute the RISC complex, which can repress specific target mRNAs. The identification of microRNA targets is of central importance, and various experimental and computational methods have been developed over the last 15 years. Most experimental methods are based on the assumption that mRNAs which interact physically with the RISC complex constitute regulatory targets and, similarly, some computational methods only aim at predicting physical interactors for RISC. Besides specific limitations, which we discuss for each method, the mere concept of assuming a functional role for every detected molecular event is likely to identify many deceptive interactions (i.e., interactions that really exist at the molecular scale, but without controlling any biological function at the macroscopic scale).In order to select biologically important interactions, some computational tools interrogate the phylogenetic conservation of microRNA/mRNA interactions, thus theoretically selecting only biologically relevant targets. Yet even comparative genomics can yield false positives.Conceptual and technical limitations for all these techniques tend to be overlooked by the scientific community. This review sums them up, emphasizing on the implications of these issues on our understanding of microRNA biology.


Assuntos
Algoritmos , Biologia Computacional/métodos , Biologia Computacional/normas , Perfilação da Expressão Gênica/métodos , MicroRNAs/genética , RNA Mensageiro/genética , Software , Regulação da Expressão Gênica , Humanos , MicroRNAs/metabolismo , RNA Mensageiro/metabolismo
13.
Genome Res ; 29(6): 999-1008, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31015259

RESUMO

The simplicity and cost-effectiveness of CRISPR technology have made high-throughput pooled screening approaches accessible to virtually any laboratory. Analyzing the large sequencing data derived from these studies, however, still demands considerable bioinformatics expertise. Various methods have been developed to lessen this requirement, but there are still three tasks for accurate CRISPR screen analysis that involve bioinformatic know-how, if not prowess: designing a proper statistical hypothesis test for robust target identification, developing an accurate mapping algorithm to quantify sgRNA levels, and minimizing the parameters that need to be fine-tuned. To make CRISPR screen analysis more reliable as well as more readily accessible, we have developed a new algorithm, called CRISPRBetaBinomial or CB2 Based on the beta-binomial distribution, which is better suited to sgRNA data, CB2 outperforms the eight most commonly used methods (HiTSelect, MAGeCK, PBNPA, PinAPL-Py, RIGER, RSA, ScreenBEAM, and sgRSEA) in both accurately quantifying sgRNAs and identifying target genes, with greater sensitivity and a much lower false discovery rate. It also accommodates staggered sgRNA sequences. In conjunction with CRISPRcloud, CB2 brings CRISPR screen analysis within reach for a wider community of researchers.


Assuntos
Sistemas CRISPR-Cas , Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Biologia Computacional , Modelos Estatísticos , Biologia Computacional/métodos , Biologia Computacional/normas , Edição de Genes , Marcação de Genes , Estudos de Associação Genética/métodos , RNA Guia , Sensibilidade e Especificidade
14.
Genome Biol ; 20(1): 47, 2019 02 27.
Artigo em Inglês | MEDLINE | ID: mdl-30813962

RESUMO

Implementation of bioinformatics software involves numerous unique challenges; a rigorous standardized approach is needed to examine software tools prior to their publication.


Assuntos
Biologia Computacional/normas , Software/normas , Arquivos
15.
PLoS Comput Biol ; 15(2): e1006803, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30759077

RESUMO

A well-established notion in cognitive neuroscience proposes that multiple brain systems contribute to choice behaviour. These include: (1) a model-free system that uses values cached from the outcome history of alternative actions, and (2) a model-based system that considers action outcomes and the transition structure of the environment. The widespread use of this distinction, across a range of applications, renders it important to index their distinct influences with high reliability. Here we consider the two-stage task, widely considered as a gold standard measure for the contribution of model-based and model-free systems to human choice. We tested the internal/temporal stability of measures from this task, including those estimated via an established computational model, as well as an extended model using drift-diffusion. Drift-diffusion modeling suggested that both choice in the first stage, and RTs in the second stage, are directly affected by a model-based/free trade-off parameter. Both parameter recovery and the stability of model-based estimates were poor but improved substantially when both choice and RT were used (compared to choice only), and when more trials (than conventionally used in research practice) were included in our analysis. The findings have implications for interpretation of past and future studies based on the use of the two-stage task, as well as for characterising the contribution of model-based processes to choice behaviour.


Assuntos
Biologia Computacional/normas , Tomada de Decisões/fisiologia , Modelos Psicológicos , Modelos Estatísticos , Tempo de Reação/fisiologia , Adolescente , Adulto , Animais , Biologia Computacional/métodos , Feminino , Humanos , Masculino , Reprodutibilidade dos Testes , Adulto Jovem
16.
BMC Genomics ; 20(Suppl 1): 82, 2019 Feb 04.
Artigo em Inglês | MEDLINE | ID: mdl-30712510

RESUMO

BACKGROUND: Existing functional description of genes are categorical, discrete, and mostly through manual process. In this work, we explore the idea of gene embedding, distributed representation of genes, in the spirit of word embedding. RESULTS: From a pure data-driven fashion, we trained a 200-dimension vector representation of all human genes, using gene co-expression patterns in 984 data sets from the GEO databases. These vectors capture functional relatedness of genes in terms of recovering known pathways - the average inner product (similarity) of genes within a pathway is 1.52X greater than that of random genes. Using t-SNE, we produced a gene co-expression map that shows local concentrations of tissue specific genes. We also illustrated the usefulness of the embedded gene vectors, laden with rich information on gene co-expression patterns, in tasks such as gene-gene interaction prediction. CONCLUSIONS: We proposed a machine learning method that utilizes transcriptome-wide gene co-expression to generate a distributed representation of genes. We further demonstrated the utility of our distribution by predicting gene-gene interaction based solely on gene names. The distributed representation of genes could be useful for more bioinformatics applications.


Assuntos
Biologia Computacional/métodos , Software , Algoritmos , Biologia Computacional/normas , Epistasia Genética , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica , Humanos , Curva ROC , Transcriptoma , Interface Usuário-Computador
17.
Genes (Basel) ; 10(2)2019 01 28.
Artigo em Inglês | MEDLINE | ID: mdl-30696086

RESUMO

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues.


Assuntos
Big Data , Biologia Computacional/métodos , Aprendizado de Máquina , Animais , Biologia Computacional/normas , Humanos
18.
Methods Mol Biol ; 1834: 29-43, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30324434

RESUMO

High-throughput transcriptome sequencing (RNASeq) represents one of the most comprehensive and scalable methods to analyze global gene expression. It allows for absolute quantification of gene expression and also enables the discovery of novel transcripts and alternatively spliced isoforms. This chapter provides hand-on tools and a step-by-step procedure to analyze RNASeq data from punctures of two different retinal tissues (retina and RPE-choroid-sclera) at two different locations (periphery and macular region) from eight individuals. The procedure described in this chapter will use various programs from the free, open-source Tuxedo Suite software package to analyze sequencing data and to ascertain genes that are differentially expressed between retina and RPE-choroid-sclera.


Assuntos
Biologia Computacional , Perfilação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Controle de Qualidade , Análise de Sequência de RNA , Software , Transcriptoma , Processamento Alternativo , Biologia Computacional/métodos , Biologia Computacional/normas , Bases de Dados Genéticas , Perfilação da Expressão Gênica/métodos , Perfilação da Expressão Gênica/normas , Regulação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Sequenciamento de Nucleotídeos em Larga Escala/normas , Análise de Sequência de RNA/métodos , Análise de Sequência de RNA/normas , Navegador
19.
Genes Immun ; 20(1): 10-22, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-29217828

RESUMO

We selected two sets of naturally occurring human missense allelic variants within innate immune genes. The first set represented eleven non-synonymous variants in six different genes involved in interferon (IFN) induction, present in a cohort of patients suffering from herpes simplex encephalitis (HSE) and the second set represented sixteen allelic variants of the IFNLR1 gene. We recreated the variants in vitro and tested their effect on protein function in a HEK293T cell based assay. We then used an array of 14 available bioinformatics tools to predict the effect of these variants upon protein function. To our surprise two of the most commonly used tools, CADD and SIFT, produced a high rate of false positives, whereas SNPs&GO exhibited the lowest rate of false positives in our test. As the problem in our test in general was false positive variants, inclusion of mutation significance cutoff (MSC) did not improve accuracy.


Assuntos
Biologia Computacional/normas , Encefalite por Herpes Simples/genética , Testes Genéticos/normas , Estudo de Associação Genômica Ampla/normas , Software/normas , Criança , Reações Falso-Positivas , Feminino , Células HEK293 , Humanos , Masculino , Mutação de Sentido Incorreto , Polimorfismo de Nucleotídeo Único , Receptores de Citocinas/genética , Receptores de Citocinas/metabolismo
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