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Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder (NDD) that is caused by genetic, epigenetic, and environmental factors. Recent advances in genomic analysis have uncovered numerous candidate genes with common…

It is of great interest to quantify the contributions of genetic variation to brain structure and function, which are usually measured by high-dimensional imaging data (e.g., magnetic resonance imaging). In addition to the variance, the…

Applications · Statistics 2020-05-05 Benjamin B. Risk , Hongtu Zhu

Flower breed detection and giving details of that breed with the suggestion of cultivation processes and the way of taking care is important for flower cultivation, breed invention, and the flower business. Among all the local flowers in…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Amena Begum Farha , Md. Azizul Hakim , Mst. Eshita Khatun

By exploiting discrete signal processing and simulating brain neuron communication, Spiking Neural Networks (SNNs) offer a low-energy alternative to Artificial Neural Networks (ANNs). However, existing SNN models, still face high…

Neural and Evolutionary Computing · Computer Science 2024-11-12 Wenxuan Pan , Feifei Zhao , Bing Han , Haibo Tong , Yi Zeng

We study the problem of detecting change points (CPs) that are characterized by a subset of dimensions in a multi-dimensional sequence. A method for detecting those CPs can be formulated as a two-stage method: one for selecting relevant…

Machine Learning · Statistics 2018-03-05 Yuta Umezu , Ichiro Takeuchi

The computational prediction of a protein structure from its sequence generally relies on a method to assess the quality of protein models. Most assessment methods rank candidate models using heavily engineered structural features, defined…

Biomolecules · Quantitative Biology 2018-11-26 Georgy Derevyanko , Sergei Grudinin , Yoshua Bengio , Guillaume Lamoureux

We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e., DNA…

Genomics · Quantitative Biology 2024-10-23 Zhihan Zhou , Weimin Wu , Harrison Ho , Jiayi Wang , Lizhen Shi , Ramana V Davuluri , Zhong Wang , Han Liu

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. In this paper, we leverage recent advances in…

In forensic genetics, short tandem repeats (STRs) are used for human identification (HID). Degraded biological trace samples with low amounts of short DNA fragments (low-quality DNA samples) pose a challenge for STR typing. Predefined…

This paper investigates the problem of adjusting for spatial effects in genomic prediction. Despite being seldomly considered in genomic prediction, spatial effects often affect phenotypic measurements of plants. We consider a Gaussian…

Applications · Statistics 2020-06-09 Xiaojun Mao , Somak Dutta , Raymond K. W. Wong , Dan Nettleton

Many DNA sequence variants influence phenotypes by altering gene expression. Our understanding of these variants is limited by sample sizes of current studies and by measurements of mRNA rather than protein abundance. We developed a…

Genomics · Quantitative Biology 2015-06-16 Frank W. Albert , Sebastian Treusch , Arthur H. Shockley , Joshua S. Bloom , Leonid Kruglyak

A general approach to selective inference is considered for hypothesis testing of the null hypothesis represented as an arbitrary shaped region in the parameter space of multivariate normal model. This approach is useful for hierarchical…

Statistics Theory · Mathematics 2018-03-28 Yoshikazu Terada , Hidetoshi Shimodaira

Genotype networks are a method used in systems biology to study the "innovability" of a set of genotypes having the same phenotype. In the past they have been applied to determine the genetic heterogeneity, and stability to mutations, of…

Populations and Evolution · Quantitative Biology 2015-06-17 Giovanni Marco Dall'Olio , Jaume Bertranpetit , Andreas Wagner , Hafid Laayouni

The widespread availability of large amounts of genomic data on the SARS-CoV-2 virus, as a result of the COVID-19 pandemic, has created an opportunity for researchers to analyze the disease at a level of detail unlike any virus before it.…

Machine Learning · Computer Science 2021-10-20 Zahra Tayebi , Sarwan Ali , Murray Patterson

Imaging genetic studies aim to find associations between genetic variants and imaging quantitative traits. Traditional genome-wide association studies (GWAS) are based on univariate statistical tests, but when multiple traits are analyzed…

Genomics · Quantitative Biology 2022-04-04 Muhammad Ammar Malik , Alexander S. Lundervold , Tom Michoel

Developments in machine learning interpretability techniques over the past decade have provided new tools to observe the image regions that are most informative for classification and localization in artificial neural networks (ANNs). Are…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Thomas A. Langlois , H. Charles Zhao , Erin Grant , Ishita Dasgupta , Thomas L. Griffiths , Nori Jacoby

Increased biosecurity and food safety requirements may increase demand for efficient traceability and identification systems of livestock in the supply chain. The advanced technologies of machine learning and computer vision have been…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Md Ekramul Hossain , Muhammad Ashad Kabir , Lihong Zheng , Dave L. Swain , Shawn McGrath , Jonathan Medway

In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 33…

Quantitative Methods · Quantitative Biology 2024-10-04 Guanao Yan , Shuo Harper Hua , Jingyi Jessica Li

In plant and animal breeding studies a distinction is made between the genetic value (additive + epistatic genetic effects) and the breeding value (additive genetic effects) of an individual since it is expected that some of the epistatic…

Applications · Statistics 2014-02-11 Deniz Akdemir

The widely used genetic pleiotropic analysis of multiple phenotypes are often designed for examining the relationship between common variants and a few phenotypes. They are not suited for both high dimensional phenotypes and high…

Machine Learning · Statistics 2015-12-04 Panpan Wang , Mohammad Rahman , Li Jin , Momiao Xiong
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