A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury
Sign Up to like & getrecommendations! Published in 2017 at "Nature Communications"
DOI: 10.1038/ncomms15932
Abstract: Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a ‘big data compacting and data fusion’—concept to capture diverse adverse outcomes on cellular and organismal levels.… read more here.
Keywords: space; gene space; transcriptomics data; drug induced ... See more keywords
STARCH: copy number and clone inference from spatial transcriptomics data
Sign Up to like & getrecommendations! Published in 2020 at "Physical Biology"
DOI: 10.1088/1478-3975/abbe99
Abstract: Tumors are highly heterogeneous, consisting of cell populations with both transcriptional and genetic diversity. These diverse cell populations are spatially organized within a tumor, creating a distinct tumor microenvironment. A new technology called spatial transcriptomics… read more here.
Keywords: copy number; spatial transcriptomics; transcriptomics data; number ... See more keywords
Performance evaluation of transcriptomics data normalization for survival risk prediction.
Sign Up to like & getrecommendations! Published in 2021 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbab257
Abstract: One pivotal feature of transcriptomics data is the unwanted variations caused by disparate experimental handling, known as handling effects. Various data normalization methods were developed to alleviate the adverse impact of handling effects in the… read more here.
Keywords: transcriptomics data; evaluation; performance; normalization ... See more keywords
Cell type identification in spatial transcriptomics data can be improved by leveraging cell-type-informative paired tissue images using a Bayesian probabilistic model
Sign Up to like & getrecommendations! Published in 2022 at "Nucleic Acids Research"
DOI: 10.1093/nar/gkac320
Abstract: Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited… read more here.
Keywords: cell; tissue images; transcriptomics data; tissue ... See more keywords
STellaris: a web server for accurate spatial mapping of single cells based on spatial transcriptomics data.
Sign Up to like & getrecommendations! Published in 2023 at "Nucleic acids research"
DOI: 10.1093/nar/gkad419
Abstract: Single-cell RNA sequencing (scRNA-seq) provides insights into gene expression heterogeneities in diverse cell types underlying homeostasis, development and pathological states. However, the loss of spatial information hinders its applications in deciphering spatially related features, such… read more here.
Keywords: cell; scrna seq; transcriptomics data; single cells ... See more keywords
In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of General Medicine"
DOI: 10.2147/ijgm.s345336
Abstract: Background Thyroid cancer is the most common endocrine malignancy. However, the molecular mechanism involved in its pathogenesis is not well characterized. Purpose The objective of this study is to identify key cellular pathways and differentially… read more here.
Keywords: ptc; transcriptomics data; thyroid cancer; analysis ... See more keywords
Sampling and ranking spatial transcriptomics data embeddings to identify tissue architecture
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.912813
Abstract: Spatial transcriptomics is an emerging technology widely applied to the analyses of tissue architecture and corresponding biological functions. Substantial computational methods have been developed for analyzing spatial transcriptomics data. These methods generate embeddings from gene… read more here.
Keywords: transcriptomics data; spatial transcriptomics; tissue architecture; sampling ranking ... See more keywords
Assessing Outlier Probabilities in Transcriptomics Data When Evaluating a Classifier
Sign Up to like & getrecommendations! Published in 2023 at "Genes"
DOI: 10.3390/genes14020387
Abstract: Outliers in the training or test set used to fit and evaluate a classifier on transcriptomics data can considerably change the estimated performance of the model. Hence, an either too weak or a too optimistic… read more here.
Keywords: classifier; outlier probabilities; probabilities transcriptomics; transcriptomics data ... See more keywords
Prediction of Metabolic Profiles from Transcriptomics Data in Human Cancer Cell Lines
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Molecular Sciences"
DOI: 10.3390/ijms23073867
Abstract: The Metabolome and Transcriptome are mutually communicating within cancer cells, and this interplay is translated into the existence of quantifiable correlation structures between gene expression and metabolite abundance levels. Studying these correlations could provide a… read more here.
Keywords: cancer; transcriptomics data; prediction; correlation ... See more keywords