Results 31 to 40 of about 2,352,277 (290)

Selecting gene features for unsupervised analysis of single-cell gene expression data

Briefings in Bioinformatics, 2021
AbstractSingle-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented molecular resolution. In order to evaluate various biological hypotheses using high-dimensional single-cell gene expression data, most computational and statistical ...
Sheng, Jie, Li, Wei Vivian
openaire   +4 more sources

Deep generative modeling for single-cell transcriptomics. [PDF]

, 2018
Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses.
A Regev, A Tanay, A Wagner, A Zeisel, AP Patel, B Wang, BK Tusi, CA Vallejos, CA Vallejos, D DeTomaso, D Grün, D Risso, DM Blei, E Pierson, FA Wolf, G Finak, G Görgün, GXY Zheng, HI Nakaya, J Ding, J Fan, Jeffrey Regier, JT Gaublomme, K Shekhar, L Haghverdi, L Held, M Stoeckius, MD Robinson, MI Love, Michael B. Cole, Michael I. Jordan, Nir Yosef, PV Kharchenko, Q Li, RE Kass, Romain Lopez, S Prabhakaran, S Semrau, U Shaham, WE Johnson   +39 more
core   +1 more source

Immune cell type signature discovery and random forest classification for analysis of single cell gene expression datasets

Frontiers in Immunology, 2023
BackgroundRobust immune cell gene expression signatures are central to the analysis of single cell studies. Nearly all known sets of immune cell signatures have been derived by making use of only single gene expression datasets.
Bogac Aybey, Bogac Aybey, Sheng Zhao, Benedikt Brors, Benedikt Brors, Eike Staub   +5 more
doaj   +1 more source

Tracking of Normal and Malignant Progenitor Cell Cycle Transit in a Defined Niche. [PDF]

, 2016
While implicated in therapeutic resistance, malignant progenitor cell cycle kinetics have been difficult to quantify in real-time. We developed an efficient lentiviral bicistronic fluorescent, ubiquitination-based cell cycle indicator reporter (Fucci2BL)
Delos Santos, Nathaniel P, Jamieson, Catriona HM, Lambert-Fliszar, Florence, Lazzari, Elisa, Lennon, Kathleen M, Marra, Marco A, Miyawaki, Atsushi, Morris, Sheldon, Pineda, Gabriel, Riso, Gennarina L, Sakaue-Sawano, Asako   +10 more
core   +1 more source

Single-cell gene expression analysis reveals diversity among human spermatogonia [PDF]

Molecular Human Reproduction, 2017
Is the molecular profile of human spermatogonia homogeneous or heterogeneous when analysed at the single-cell level?Heterogeneous expression profiles may be a key characteristic of human spermatogonia, supporting the existence of a heterogeneous stem cell population.Despite the fact that many studies have sought to identify specific markers for human ...
N, Neuhaus, J, Yoon, N, Terwort, S, Kliesch, J, Seggewiss, A, Huge, R, Voss, S, Schlatt, R V, Grindberg, H R, Schöler   +9 more
openaire   +2 more sources

Generalized gene co-expression analysis via subspace clustering using low-rank representation [PDF]

, 2019
BACKGROUND: Gene Co-expression Network Analysis (GCNA) helps identify gene modules with potential biological functions and has become a popular method in bioinformatics and biomedical research.
Huang, Kun, Wang, Tongxin, Zhang, Jie
core   +1 more source

Modeling bi-modality improves characterization of cell cycle on gene expression in single cells. [PDF]

PLoS Computational Biology, 2014
Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level.
Andrew McDavid, Lucas Dennis, Patrick Danaher, Greg Finak, Michael Krouse, Alice Wang, Philippa Webster, Joseph Beechem, Raphael Gottardo   +8 more
doaj   +1 more source

Insights on the Control of Yeast Single-Cell Growth Variability by Members of the Trehalose Phosphate Synthase (TPS) Complex

Frontiers in Cell and Developmental Biology, 2021
Single-cell variability of growth is a biological phenomenon that has attracted growing interest in recent years. Important progress has been made in the knowledge of the origin of cell-to-cell heterogeneity of growth, especially in microbial cells.
Sevan Arabaciyan, Michael Saint-Antoine, Cathy Maugis-Rabusseau, Jean-Marie François, Abhyudai Singh, Jean-Luc Parrou, Jean-Pascal Capp   +6 more
doaj   +1 more source

Co-expression networks in generation of induced pluripotent stem cells. [PDF]

, 2016
We developed an adenoviral vector, in which Yamanaka's four reprogramming factors (RFs) were controlled by individual CMV promoters in a single cassette (Ad-SOcMK). This permitted coordinated expression of RFs (SOX2, OCT3/4, c-MYC and KLF4) in a cell for
Coppola, Giovanni, Dansithong, Warunee, Figueroa, Karla P, Gao, Fuying, Paul, Sharan, Pflieger, Lance, Pulst, Stefan M   +6 more
core   +2 more sources

Processing, visualising and reconstructing network models from single-cell data. [PDF]

, 2015
New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational
Fisher, Jasmin, Göttgens, Berthold, Moignard, Victoria, Woodhouse, Steven   +3 more
core   +2 more sources