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  2. Single-cell sequencing - Wikipedia

    en.wikipedia.org/wiki/Single-cell_sequencing

    Single-cell DNA genome sequencing involves isolating a single cell, amplifying the whole genome or region of interest, constructing sequencing libraries, and then applying next-generation DNA sequencing (for example Illumina, Ion Torrent). Single-cell DNA sequencing has been widely applied in mammalian systems to study normal physiology and ...

  3. Single-cell multi-omics integration - Wikipedia

    en.wikipedia.org/wiki/Single-cell_multi-omics...

    Single-cell omics technologies has extended beyond the transcriptome to profile diverse physical-chemical properties at single-cell resolution, including whole genomes/exomes, DNA methylation, chromatin accessibility, histone modifications, epitranscriptome (e.g., mRNAs, microRNAs, tRNAs, lncRNAs), proteome, phosphoproteome, metabolome, and more.

  4. Single-cell analysis - Wikipedia

    en.wikipedia.org/wiki/Single-cell_analysis

    This single cell shows the process of the central dogma of molecular biology, which are all steps researchers are interested to quantify (DNA, RNA, and Protein).. In cell biology, single-cell analysis and subcellular analysis [1] refer to the study of genomics, transcriptomics, proteomics, metabolomics, and cellcell interactions at the level of an individual cell, as opposed to more ...

  5. Single-cell transcriptomics - Wikipedia

    en.wikipedia.org/wiki/Single-cell_transcriptomics

    As a result of the aforementioned properties of single-cell transcriptomic data, batch correction methods developed for bulk sequencing data were observed to perform poorly. Consequently, researchers developed statistical methods to correct for batch effects that are robust to the properties of single-cell transcriptomic data to integrate data ...

  6. Hi-C (genomic analysis technique) - Wikipedia

    en.wikipedia.org/wiki/Hi-C_(genomic_analysis...

    Overall, this technique circumvents the issue of requiring a high cell number input for Hi-C and the high sequencing depth required to obtain high resolution data, but can only achieve resolutions of up to 5 kb and may not always be reproducible due the variable nature of sample sizes used and the data generated from it. [23] Figure 4. Overview ...

  7. EPIC-Seq - Wikipedia

    en.wikipedia.org/wiki/EPIC-Seq

    EPIC-seq, (short for Epigenetic Expression Inference by Cell-free DNA Sequencing), is a high-throughput method that specifically targets gene promoters using cell-free DNA (cfDNA) sequencing. By employing non-invasive techniques such as blood sampling , it infers the expression levels of targeted genes .

  8. Trajectory inference - Wikipedia

    en.wikipedia.org/wiki/Trajectory_inference

    Trajectory inference as implemented in Slingshot for (a) a simulated two-dimensional dataset and (b) a single-cell RNA-seq dataset of the olfactory epithelium.. Trajectory inference or pseudotemporal ordering is a computational technique used in single-cell transcriptomics to determine the pattern of a dynamic process experienced by cells and then arrange cells based on their progression ...

  9. List of model organisms - Wikipedia

    en.wikipedia.org/wiki/List_of_model_organisms

    Stentor coeruleus, used in molecular biology (its genome has been sequenced), [5] and is studied as a model of single-cell regeneration.; Dictyostelium discoideum, used in molecular biology and genetics (its genome has been sequenced), and is studied as an example of cell communication, differentiation, and programmed cell death.

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