Imputation integrates single-cell and spatial gene expression data to resolve transcriptional networks in barley shoot meristem development. [PDF]
Demesa-Arevalo E +11 more
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UiO‐66(Zr) metal–organic frameworks are chemically stable, biocompatible, and highly tunable nanomaterials. Their modular structure enables controlled drug delivery, multimodal bioimaging, and light‐activated photodynamic therapy, supporting integrated diagnostic and therapeutic (theranostic) applications in cancer and biomedical research.
Veronika Huntošová +2 more
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Improving prediction of bacterial sRNA regulatory targets with expression data. [PDF]
Derinkok Y, Wang H, Tjaden B.
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circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data. [PDF]
Ryšavý P +3 more
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CYCLONE: recycle contrastive learning for integrating single-cell gene expression data. [PDF]
Ji H, He X, Li H.
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Protocol to predict the origin of cancer of unknown primary from gene expression data using BPformer. [PDF]
Xie J +5 more
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Deep learning-based Alzheimer's disease detection using magnetic resonance imaging and gene expression data. [PDF]
Almarri B.
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Harmonizing heterogeneous single-cell gene expression data with individual-level covariate information. [PDF]
Mu Y, Li WV.
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Expressiveness in conceptual data modelling
Data & Knowledge Engineering, 1993Summary: Conceptual data modelling techniques aim at the representation of data at a high level of abstraction. The conceptualisation principle states that only those aspects are to be represented that deal with the meaning of the universe of discourse. Conventional data modelling techniques, as e.g.
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Analysis of Expression Data: An Overview
Current Protocols in Bioinformatics, 2003AbstractAfter providing a brief introduction to microarray chips and experimental details, this overview discusses analysis techniques. Data analysis from microarray experiments generally involves two parts: acquiring and normalizing the data, and interpreting it. This unit focuses mostly on the latter, as it is less technology‐specific.
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