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Search · four archives
24 papers · ranked by Valyu relevance
Yi Zhong, Ying-Wooi Wan, Kaifang Pang, Lionel ML Chow + 1 more
Background Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in…
Oyetunji E. Ogundijo, Xiaodong Wang, Lars Kaderali
High-throughput gene expression data are often obtained from pure or complex (heterogeneous) biological samples. In the latter case, data obtained are a mixture of different cell types and the heterogeneity imposes some difficulties in the analysis of such data. In order to make conclusions on gene expresssion data…
Maria K Jaakkola, Laura L Elo
Computational deconvolution is a time and cost-efficient approach to obtain cell type-specific information from bulk gene expression of heterogeneous tissues like blood. Deconvolution can aim to either estimate cell type proportions or abundances in samples, or estimate how strongly each present cell type expresses…
Konstantin Zaitsev, Monika Bambouskova, Amanda Swain, Maxim N. Artyomov
Changes in bulk transcriptional profiles of heterogeneous samples often reflect changes in proportions of individual cell types. Several robust techniques have been developed to dissect the composition of such mixed samples given transcriptional signatures of the pure components or their proportions. These approaches…
Artur Gynter, Dimitri Meistermann, Harri Lähdesmäki, Helena Kilpinen
Bulk RNA-Seq remains a widely adopted technique to profile gene expression, primarily due to the persistent challenges associated with achieving single-cell resolution. However, a key challenge is accurately estimating the proportions of different cell types within these bulk samples. To address this issue, we…
Wei Zhang, Xianglin Zhang, Qiao Liu, Lei Wei + 4 more
In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available…
Vimalathithan Devaraj, Biplab Bose
The expression of a gene is commonly estimated by quantitative PCR (qPCR) using RNA isolated from a large number of pooled cells. Such pooled samples often have subpopulations of cells with different levels of expression of the target gene. Estimation of gene expression from an ensemble of cells obscures the pattern of…
Joshua T Burdick, John Isaac Murray
Background Knowledge of when and in which cells each gene is expressed across multicellular organisms is critical in understanding both gene function and regulation of cell type diversity. However, methods for measuring expression typically involve a trade-off between imaging-based methods, which give the precise…
Patrick Danaher, Youngmi Kim, Brenn Nelson, Maddy Griswold + 3 more
We introduce SpatialDecon, an algorithm for quantifying cell populations defined by single cell RNA sequencing within the regions of spatially-resolved gene expression studies. It obtains cell abundance estimates that are spatially-resolved, granular, and paired with highly multiplexed gene expression data.…
Andrea Blasco, Ted Natoli, Michael G. Endres, Rinat A. Sergeev + 6 more
A recurring problem in biomedical research is how to isolate signals of distinct populations (cell types, tissues, and genes) from composite measures obtained by a single analyte or sensor. Existing computational deconvolution approaches work well in many specific settings, but they might be suboptimal in more general…
Shahin Mohammadi, Neta S. Zuckerman, Andrea Goldsmith, Ananth Grama
—Identifying properties and concentrations of components from an observed mixture, known as deconvolution, is a fundamental problem in signal processing. It has diverse applications in fields ranging from hyperspectral imaging to denoising readings from biomedical sensors. This paper focuses on in-silico deconvolution…
Niya Wang, Eric P. Hoffman, Robert Clarke, Zhen Zhang + 6 more
'David M. Herrington' 'Ie‐Ming Shih' 'Douglas A. Levine' 'Guoqiang Yu' 'Jianhua Xuan' 'Yue Wang'] 1 Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA; 2 Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC 20010, USA; 3 Lombardi Comprehensive…
Lisa Buchauer, Shalev Itzkovitz
We introduce cellanneal, a python-based software for deconvolving bulk RNA sequencing data. cellanneal relies on the optimization of Spearman's rank correlation coefficient between experimental and computational mixture gene expression vectors using simulated annealing. cellanneal can be used as a python package or via…
Nico Riedel, Johannes Berg
In a multicellular organism different cell types express a gene in different amounts. Samples from which gene expression levels can be measured typically contain a mixture of different cell types, the resulting measurements thus give only averages over the different cell types present. Based on fluctuations in the…
Biao Cai, Jingfei Zhang, Hongyu Li, Chang Su + 1 more
There is a growing interest in cell-type-specific analysis from bulk samples with a mixture of different cell types. A critical first step in such analyses is the accurate estimation of cell-type proportions in a bulk sample. Although many methods have been proposed recently, quantifying the uncertainties associated…
Manuel Schölling, Rudolf Hanel
Motivation: Gene transcription requires the orchestrated binding of various proteins to the promoter of a gene. The binding times and binding order of proteins allow to draw conclusions about the proteins' exact function in the recruitment process. Time-resolved ChIP experiments are being used to analyze the order of…
Joana Godinho, Alexandra M. Carvalho, Susana Vinga
In the field of molecular biology, genomic signature analysis is a powerful mean to unravel obscured cellular aspects. One of the main tasks in gene expression analysis is the exploration of transcriptomic data, which enables the recognition of genes that are differentially expressed (DEG). Disease profiling, treatment…
Authors not listed
Electrospray ionization (ESI) mass spectrometry is an essential technique for chemical analysis in a range of fields. In ESI, analytes can produce multiple charge states, which must be correctly assigned for identification. Existing approaches to charge state assignment can suffer from limited accuracy and/or poor…
Marcelo Boareto, Nestor Caticha, Xin Ma
Microarray data analysis typically consists in identifying a list of differentially expressed genes (DEG), i.e., the genes that are differentially expressed between two experimental conditions. Variance shrinkage methods have been considered a better choice than the standard t-test for selecting the DEG because they…
Adeleke Maradesa, Baptiste Py, Ting Hei Wan, Mohammed B. Effat + 1 more
Electrochemical impedance spectroscopy (EIS) is a characterization technique used widely in electrochemistry. Obtaining EIS data is simple when modern electrochemical workstations are used; however, analyzing EIS spectra is still a considerable quandary. The distribution of relaxation times (DRT) has emerged as a…
Griffin Chure, Jonas Cremer
High-Performance Liquid Chromatography (HPLC) and Gas Chromatography are analytical techniques which allow for the quantitative characterization of the chemical components of mixtures . Technological advancements in sample preparation and mechanical automation have allowed HPLC to become a high-throughput tool which…
Denice van Herwerden, Jake O'Brien, Sascha Lege, Bob Pirok + 2 more
Fragment deconvolution is a crucial step during componentization of non-targeted analysis (NTA) high-resolution mass spectrometry (HRMS) data, aiming to filter out false positive (FP) signals that do not belong to the component. Moreover, inclusion of FP fragments could lead to, for example, wrong identification…
Authors not listed
Electrochemical impedance spectroscopy (EIS) coupled with distribution of relaxation times (DRT) analysis is a robust framework for characterizing electrochemical systems. However, DRT deconvolution is often plagued by spurious peaks, hindering accurate process identification and quantitative parameter estimation. To…
Zahir Ali, Maged Serag, Gozde Demirer, Bruno Torre + 4 more
Efficient delivery of DNA, RNA, and genome engineering machinery to plant cells will enable efforts to genetically modify plants for global food security, sustainable energy production, synthetic biology applications, and climate change resilience. For the delivery of functional genetic units into plant cells, charged…