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Gene finding is the task of identifying the locations of coding sequences within the vast amount of genetic code contained in the genome. With an ever increasing quantity of raw genome sequences, gene finding is an important avenue towards…

Genomics · Quantitative Biology 2025-05-07 Frederikke I. Marin , Dennis Pultz , Wouter Boomsma

Building prediction models for outcomes of clinical relevance when only a limited number of mutational features are available causes considerable challenges due to the sparseness and low-dimensionality of the data. In this article, we…

Genomics · Quantitative Biology 2022-12-13 Maya Ramchandran , Maayan Baron

Networks of genetic expression can be modelled by hypergraphs with the additional structure that real coefficients are given to each vertex-edge incidence. The spectra, i.e. the multiset of the eigenvalues, of such hypergraphs, are known to…

Molecular Networks · Quantitative Biology 2021-09-24 Raffaella Mulas , Michael J. Casey

Graphs are crucial for representing interrelated data and aiding predictive modeling by capturing complex relationships. Achieving high-quality graph representation is important for identifying linked patterns, leading to improvements in…

Machine Learning · Computer Science 2024-07-23 Sumeyye Bas , Kiymet Kaya , Resul Tugay , Sule Gunduz Oguducu

Exploratory data analysis is a fundamental aspect of knowledge discovery that aims to find the main characteristics of a dataset. Dimensionality reduction, such as manifold learning, is often used to reduce the number of features in a…

Neural and Evolutionary Computing · Computer Science 2019-10-24 Andrew Lensen , Bing Xue , Mengjie Zhang

In the present work we have selected a collection of statistical and mathematical tools useful for the exploration of multivariate data and we present them in a form that is meant to be particularly accessible to a classically trained…

Statistics Theory · Mathematics 2010-09-01 Magnus Fontes

Electron and scanning probe microscopy produce vast amounts of data in the form of images or hyperspectral data, such as EELS or 4D STEM, that contain information on a wide range of structural, physical, and chemical properties of…

Machine Learning · Computer Science 2023-06-09 Arpan Biswas , Maxim Ziatdinov , Sergei V. Kalinin

Background: Evidence maps have been used in healthcare to understand existing evidence and to support decision-making. In oncology they have been used to summarise evidence within a disease area but have not been used to compare evidence…

In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent…

Methodology · Statistics 2019-03-27 Naim U. Rashid , Quefeng Li , Jen Jen Yeh , Joseph G. Ibrahim

How to represent the genetic code? Despite the fact that it is extensively known, the DNA mapping into proteins remains as one of the relevant discoveries of genetics. However, modern genomic signal processing usually requires converting…

Other Quantitative Biology · Quantitative Biology 2015-03-10 H. M. de Oliveira , N. S. Santos-Magalhaes

We introduce OrigamiPlot, an open-source R package and Shiny web application designed to enhance the visualization of multivariate data. This package implements the origami plot, a novel visualization technique proposed by Duan et al. in…

Human-Computer Interaction · Computer Science 2024-11-20 Yiwen Lu , Jiayi Tong , Yuqing Lei , Alex J. Sutton , Haitao Chu , Lisa D. Levine , Thomas Lumley , David A. Asch , Rui Duan , Christopher H. Schmid , Yong Chen

Manifold alignment (MA) involves a set of techniques for learning shared representations across domains, yet many traditional MA methods are incapable of performing out-of-sample extension, limiting their real-world applicability. We…

Machine Learning · Computer Science 2025-09-30 Jake S. Rhodes , Adam G. Rustad , Marshall S. Nielsen , Morgan Chase McClellan , Dallan Gardner , Dawson Hedges

Transcriptomic data is a treasure-trove in modern molecular biology, as it offers a comprehensive viewpoint into the intricate nuances of gene expression dynamics underlying biological systems. This genetic information must be utilised to…

Molecular Networks · Quantitative Biology 2023-12-13 Vikram Singh , Vikram Singh

Variable importance, interaction measures, and partial dependence plots are important summaries in the interpretation of statistical and machine learning models. In this paper we describe new visualization techniques for exploring these…

Computation · Statistics 2021-10-12 Alan Inglis , Andrew Parnell , Catherine Hurley

Although there are established graphics that accompany the most common functional data analyses, generating these graphics for each dataset and analysis can be cumbersome and time consuming. Often, the barriers to visualization inhibit…

Other Statistics · Statistics 2016-02-15 Julia Wrobel , So Young Park , Ana Maria Staicu , Jeff Goldsmith

The linking genotype to phenotype is the fundamental aim of modern genetics. We focus on study of links between gene expression data and phenotype data through integrative analysis. We propose three approaches. 1) The inherent complexity of…

Quantitative Methods · Quantitative Biology 2015-06-30 Min Xu

Modern display environments offer great potential for involving multiple users in presentations, discussions, and data analysis sessions. By showing multiple views on multiple displays, information exchange can be improved, several…

Graphics · Computer Science 2019-12-19 Christian Eichner , Heidrun Schumann , Christian Tominski

In order to improve the advantages and the reliability of the second derivative method in tracking the position of extrema from experimental curves, we develop a novel analysis method based on the mathematical concept of curvature. We…

Data Analysis, Statistics and Probability · Physics 2011-05-04 P. Zhang , P. Richard , T. Qian , Y. -M. Xu , X. Dai , H. Ding

A prespecified set of genes may be enriched, to varying degrees, for genes that have altered expression levels relative to two or more states of a cell. Knowing the enrichment of gene sets defined by functional categories, such as gene…

Random feature maps are ubiquitous in modern statistical machine learning, where they generalize random projections by means of powerful, yet often difficult to analyze nonlinear operators. In this paper, we leverage the "concentration"…

Machine Learning · Statistics 2021-03-18 Zhenyu Liao , Romain Couillet
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