13 papers · ranked by Valyu relevance
Faezeh Moradi, Kambiz Pourrezaei
An objective approach for odor detection is to analyze the brain activity using imaging techniques during the odor stimulation. In this study, Functional Near Infrared Spectroscopy (fNIRS) is used to record hemodynamic response from the frontal region of the brain by using a 4-channel fNIRS system. The fNIRs data is…
Kyungmin Ahn, Hironobu Fujiwara
In single-cell RNA-sequencing (scRNA-seq) data analysis, a number of statistical tools in multivariate data analysis (MDA) have been developed to help analyze the gene expression data. This MDA approach is typically focused on examining discrete genomic units of genes that ignores the dependency between the data…
Danni Tu, Julia Wrobel, Theodore D. Satterthwaite, Jeff Goldsmith + 5 more
In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and…
Simone Pernice, Roberta Sirovich, Elena Grassi, Marco Viviani + 10 more
The transition from the evaluation of a single time point to the examination of the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and data clustering…
Benjamin Tenmann, Karina Close, Andrea Rodriguez-Martinez, Samer Abujudeh
Advancements in Genome-wide association studies (GWAS) have led to the discovery of numerous genetic variants potentially linked to various traits, necessitating effective methods to interpret and summarise these vast data sets. We introduce funkea, a Python package designed to fill this need by providing functional…
Yodit Feseha, Quentin Moiteaux, Estelle Geffard, Gérard Ramstein + 2 more
Web-based data analysis and visualization tools are mostly designed for specific purposes, such as data from whole transcriptome RNA sequencing or single-cell RNA sequencing. However, limited efforts have been made to develop tools designed for data of common laboratory data for non-computational scientists. The…
Suhas V. Vasaikar, Adam K. Savage, Qiuyu Gong, Elliott Swanson + 10 more
Longitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its many intrinsic types of variations. We present PALMO (https://github.com/aifimmunology/PALMO), a platform that contains five analytical modules to examine longitudinal…
Eric Schulz, Joshua B. Tenenbaum, David Duvenaud, Maarten Speekenbrink + 1 more
How do people recognize and learn about complex functional structure? Taking inspiration from other areas of cognitive science, we propose that this is achieved by harnessing compositionality: complex structure is decomposed into simpler building blocks. We formalize this idea within the framework of Bayesian…
Max Robinson, Anat Zimmer, Terry Farrah, Denise E. Mauldin + 3 more
Scale invariance is a common property of physical laws and a key concept in perspective drawing, which aims to provide a meaningful two-dimensional representation of a more complex, three-dimensional scene. Here we describe Scale Invariant Geometric Data Analysis (SIGDA), a new, general exploratory data analysis (EDA)…
Denis Polunin, Irina Shtaiger, Vadim Efimov
Biologists more and more have to deal with objects with non-numeric descriptions: texts (e.g. genetic sequences or even whole genomes), graphs, images, etc. There even could be no variables or descriptions at all when variability of objects is defined by similarity matrix. It is also possible to have too many variables…
Thomas P. Quinn, Ionas Erb
In the health sciences, many data sets produced by next-generation sequencing (NGS) only contain relative information because of biological and technical factors that limit the total number of nucleotides observed for a given sample. As mutually dependent elements, it is not possible to interpret any component in…
Shamus M. Cooley, Timothy Hamilton, J. Christian J. Ray, Eric J. Deeds
High-dimensional data are becoming increasingly common in nearly all areas of science. Developing approaches to analyze these data and understand their meaning is a pressing issue. This is particularly true for the rapidly growing field of single-cell RNA-Seq (scRNA-Seq), a technique that simultaneously measures the…
Alina Malyutina, Jing Tang, Ali Amiryousefi
Classic Analysis of Variance (ANOVA; cA) tests the explanatory power of a partitioning on a set of objects. Nonparametric ANOVA (npA) extends to a case where instead of the object values themselves, their mutual distances are available. While considerably widening the applicability of the cA, the npA does not provide a…