20 papers · ranked by Valyu relevance
Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu
Estimating the true rank of a noisy data matrix is a fundamental problem underlying techniques such as principal component analysis, matrix completion, etc. Existing rank estimation criteria, including information-based and cross-validation methods, are either highly sensitive to outliers or computationally demanding…
R. Balamurugan
Microarray gene expression data are high-dimensional and complex, with patterns that may appear only under specific conditions. Traditional clustering often misses these local patterns, whereas biclustering can reveal groups of genes with coordinated expression across particular conditions. In this paper, we propose a…
Simo Inkala, Antonio Federico, Angela Serra, Dario Greco
This study provides manually curated and homogenised transcriptomics data of interstitial lung disease (ILD) patients retrieved from the NCBI Gene Expression Omnibus and European Nucleotide Archive repositories. The compendium includes 30 transcriptomics datasets generated with DNA microarrays and RNA sequencing…
A S Escobedo-Muñoz, Diego Carmona-Campos, Armando G G Trapaga, Julio A Freyre-González
The Gene Expression Omnibus (GEO) is the largest functional genomics repository, including ~5 million entries related to the main transcriptomic technologies: microarrays and RNA-seq. This amount of data has the potential to be reused in large-scale meta-analysis, such as those in bacterial systems biology, where the…
Shuchi Wu, Xing Yi, Song Li, Bingyu Zhao
Plant papain-like cysteine proteases (PLCPs) and cystatins constitute a major protease-inhibitor system that contributes to plant signaling and responses to biotic and abiotic stress. Although the Arabidopsis genome encodes 31 predicted PLCPs and 7 cystatins, their coordinated regulation has not been systematically…
Neeraja M. Krishnan, Sarah I Rahman, Lars Røn Olsen, Binay Panda
Many biological studies could benefit from combining data from legacy microarray and high-throughput sequencing platforms, especially in clinical domains where collecting additional samples is not possible. However, incompatibility between platforms makes legacy data difficult to integrate, owing to differences in…
Jarno Koetsier, Ozan Cinar, Egon L. Willighagen, Ammar Ammar + 7 more
Transcriptomic profiling has become a cornerstone of modern biomedical research. To make transcriptomic analyses accessible to a broader scientific community, specifically including researchers with limited bioinformatics expertise, we introduced ArrayAnalysis in 2013 as a user-friendly web-based application for…
Mahboube Akhlaghi, Erfan Ghasemi, Meghana S. Ray, Saumyadipta Pyne
High-throughput transcriptomic analysis has benefited from many statistical tests of differential gene expression across two or more groups such as t tests, ANOVA, etc. Yet, in complex transcriptomic datasets such as multi-group longitudinal measures, few studies have addressed such key issues as group effects and…
Erika Schaudy, Jory Lietard
Chemically modifying the backbone, sugar, or nucleobase moieties of nucleic acids greatly expands their functional repertoire. Nucleobase modifications have received particular attention for their proven ability to generate a greater diversity of intra- and intermolecular interactions. This broader interaction…
Ícaro S. Lopes, Eduardo R. Fukutani, Tiago F. Mota, Bruno B. Andrade + 3 more
The omics sciences represent a revolution for clinical studies, offering integrative approaches to analyzing biological data with unprecedented depth. From the discovery of the double-helix structure of DNA to the CRISPR-Cas9 gene editing tool, passing through the evolution of sequencing platforms and the exponential…
Arianna L. Williams-Katek, Saahithi Mallapragada, Evan D. Mee, Brandon K. Fischer + 5 more
Spatial transcriptomics faces a trade-off between the number of genes assayed and depth of per-gene sensitivity. We developed a ‘dual chemistry’ method that combines the high sensitivity of a 10X Genomics Xenium V1 custom panel (up to 480 genes) with the broad coverage of the Prime 5K panel (5001 genes) on a single…
Hope A. Townsend, Kimberly R. Jordan, Rebecca J. Wolsky, Lucy B. Van Kleunen + 6 more
The clinical heterogeneity of cancer poses a major challenge for precision medicine. Limited cohort sizes across evolving assay platforms impede reliable biomarker discovery. Here, we systematically evaluate how to integrate data from four transcriptomics platforms: bulk and single-cell (sc) RNA sequencing (RNA-seq)…
Santra Santhosh, Sharon Istvánffy, Omer Sabary, Eitan Yaakobi + 3 more
Large-scale de novo nucleic acid synthesis is a powerful tool enabling researchers to better understand and engineer biological systems. Fields ranging from genomics to nucleic acid therapeutics to synthetic biology make use of high-throughput experimental approaches requiring access to large pools or libraries of DNA…
Mikhail Sokolov, Irina S. Kriukova, Alyona Sukhanova, Igor Nabiev
Suspension microarrays based on optically encoded microbeads have become one of the most versatile platforms for multiplexed bioanalysis because they combine solution-phase reaction kinetics, flexible assay design, and high-throughput detection. However, despite more than two decades of intense research, no consensus…
Morgan L. Turner, Thomas Chris Smits, Tiffany Liaw, Brendan Honick + 45 more
Authors: Morgan L. Turner 1 , Thomas C. Smits 1 , Tiffany S. Liaw 1 , Brendan Honick 2 , Bill Shirey 3 , Lisa Choy 1 , Nikolay Akhmetov 1 , Shaokun An 4 , David Betancur 2 , Dominic Bordelon 2 , Karl Burke 3 , Ivan Cao-Berg 2 , John Conroy 1 , Chris Csonka 2 , Penny Cuda 5 , Sean Donahue 5 , Stephen Fisher 6 , Derek…
Huanfei Wang, Shixue Sun, Ewy A. Mathé, Qian Zhu
Rare diseases (RD) impact over 30 million individuals in the United States, yet fewer than 5% of the identified conditions have FDA-approved treatments. Progress in RD research is hindered by small patient cohorts, biological heterogeneity, and the fragmented, inconsistently annotated publicly available omics data…
Pritam Dey, Rajarshi Guhaniyogi, Yang Ni, Bani K. Mallick
Spatially resolved transcriptomics is a fast-developing set of technologies that enables the measurement of localized gene expression across spatial locations in a sample. Detecting spatially varying genes is critical for analyzing such data, yet existing methods often fail to account for inter-gene correlations…
Athanasios Angelakis
Differential-expression analyses often turn cohort-specific significance into claims of stable gene signatures or diagnostic biomarkers. We evaluated which layers of evidence reproduce across independent datasets and whether discovery-derived panels retain locked tumor-versus-non-tumor classification performance. Nine…
Najla Abassi, Lea Schwarz, Filippi, Edoardo + 1 more
Summary: Modern omics experiments now involve multiple conditions and complex designs, producing an increasingly large set of differential expression and functional enrichment analysis results. However, no standardized data structure exists to store and contextualize these results together with their metadata, leaving…
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Understanding how plants respond to dynamic and spatially variable stimuli is a key goal in plant sciences. Traditional imaging methods often involve a trade-off between environmental control and spatial resolution, limiting their ability to capture real-time responses in high resolution. Microfluidic technology…