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Genome-Wide Association Studies (GWAS) help identify genetic variations in people with diseases such as Parkinson's disease (PD), which are less common in those without the disease. Thus, GWAS data can be used to identify genetic variations…

Genomics · Quantitative Biology 2023-04-07 Ali Amelia , Lourdes Pena-Castillo , Hamid Usefi

Genome-wide association study (GWAS) tests single nucleotide polymorphism (SNP) markers across the genome to localize the underlying causal variant of a trait. Because causal variants are seldom observed directly, a surrogate model based on…

Populations and Evolution · Quantitative Biology 2023-03-03 Hanbin Lee , Moo Hyuk Lee

The genetic code refers to a rule that maps 64 codons to 20 amino acids. Nearly all organisms, with few exceptions, share the same genetic code, the standard genetic code (SGC). While it remains unclear why this universal code has arisen…

Populations and Evolution · Quantitative Biology 2023-05-10 Yuji Omachi , Nen Saito , Chikara Furusawa

Because of the high cost of commercial genotyping chip technologies, many investigations have used a two-stage design for genome-wide association studies, using part of the sample for an initial discovery of ``promising'' SNPs at a less…

Background: Haplotypes, the ordered lists of single nucleotide variations that distinguish chromosomal sequences from their homologous pairs, may reveal an individual's susceptibility to hereditary and complex diseases and affect how our…

Social and Information Networks · Computer Science 2019-11-28 Abishek Sankararaman , Haris Vikalo , François Baccelli

The widespread use of generalized linear models in case-control genetic studies has helped identify many disease-associated risk factors typically defined as DNA variants, or single nucleotide polymorphisms (SNPs). Up to now, most…

Applications · Statistics 2019-03-05 Chao Zheng , Davide Ferrari , Michael Zhang , Paul Baird

The noval method for mutational disease prediction using bioinformatics tools and datasets for diagnosis the malignant mutations with powerful Artificial Neural Network (Backpropagation Network) for classifying these malignant mutations are…

Computational Engineering, Finance, and Science · Computer Science 2013-06-11 Ayad Ghany Ismaeel , Anar Auda Ablahad

In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is a heterogeneous disease. Examining similarity and difference in the genetic basis of multiple subtypes of…

Methodology · Statistics 2013-04-18 Jin Liu , Jian Huang , Yawei Zhang , Qing Lan , Nathaniel Rothman , Tongzhang Zheng , Shuangge Ma

Natural populations often show enhanced genetic drift consistent with a strong skew in their offspring number distribution. The skew arises because the variability of family sizes is either inherently strong or amplified by population…

Populations and Evolution · Quantitative Biology 2022-01-13 Takashi Okada , Oskar Hallatschek

The detection of rare variants is important for understanding the genetic heterogeneity in mixed samples. Recently, next-generation sequencing (NGS) technologies have enabled the identification of single nucleotide variants (SNVs) in mixed…

Genomics · Quantitative Biology 2016-04-25 Fan Zhang , Patrick Flaherty

Advanced Persistent Threats (APTs) are sophisticated, long-term cyberattacks that are difficult to detect because they operate stealthily and often blend into normal system behavior. This paper presents a neuro-symbolic anomaly detection…

Machine Learning · Computer Science 2026-02-17 Asif Tauhid , Sidahmed Benabderrahmane , Mohamad Altrabulsi , Ahamed Foisal , Talal Rahwan

The emergence of a predominant phenotype within a cell population is often triggered by a rare accumulation of DNA mutations in a single cell. For example, tumors may be initiated by a single cell in which multiple mutations cooperate to…

Tissues and Organs · Quantitative Biology 2018-11-21 Philip Greulich , Benjamin D. Simons

Reproducibility in genome-wide association studies (GWAS) is crucial for ensuring reliable genomic research outcomes. However, limited access to original genomic datasets (mainly due to privacy concerns) prevents researchers from…

Genomics · Quantitative Biology 2024-11-19 Yuzhou Jiang , Erman Ayday

Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters…

Methodology · Statistics 2020-05-26 Minjie Wang , Tianyi Yao , Genevera I. Allen

Amortized Bayesian inference (ABI) offers fast, scalable approximations to posterior densities by training neural surrogates on data simulated from the statistical model. However, ABI methods are highly sensitive to model misspecification:…

Machine Learning · Statistics 2026-01-27 Šimon Kucharský , Aayush Mishra , Daniel Habermann , Stefan T. Radev , Paul-Christian Bürkner

With the advance of high-throughput sequencing technologies, it has become feasible to investigate the influence of the entire spectrum of sequencing variations on complex human diseases. Although association studies utilizing the new…

Methodology · Statistics 2025-08-19 Ming Li , Zihuai He , Min Zhang , Xiaowei Zhan , Changshuai Wei , Robert C Elston , Qing Lu

In a coupled-channel model, we explore the effects of coupling between configurations on the radial behavior of the wave function and, in particular, on the spectroscopic factor (SF) and the asymptotic normalization coefficient (ANC). We…

Nuclear Theory · Physics 2010-12-10 P. Capel , P. Danielewicz , F. M. Nunes

Affected relatives are essential for pedigree linkage analysis, however, they cause a violation of the independent sample assumption in case-control association studies. To avoid the correlation between samples, a common practice is to take…

Quantitative Methods · Quantitative Biology 2011-05-03 Yaning Yang , Elaine F. Remmers , Chukwuma B. Ogunwole , Daniel L. Kastner , Peter K. Gregersen , Wentian Li

Disease-gene association through Genome-wide association study (GWAS) is an arduous task for researchers. Investigating single nucleotide polymorphisms (SNPs) that correlate with specific diseases needs statistical analysis of associations.…

Quantitative Methods · Quantitative Biology 2020-12-21 Sezin Kircali Ata , Min Wu , Yuan Fang , Le Ou-Yang , Chee Keong Kwoh , Xiao-Li Li

The attributable fraction among the exposed (\textbf{AF}$_e$), also known as the attributable risk or excess fraction among the exposed, is the proportion of disease cases among the exposed that could be avoided by eliminating the exposure.…

Methodology · Statistics 2024-12-30 Kan Chen , Jing Cheng , M. Elizabeth Halloran , Dylan S. Small
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