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  2. Single-cell sequencing - Wikipedia

    en.wikipedia.org/wiki/Single-cell_sequencing

    Single-cell sequencing examines the nucleic acid sequence information from individual cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. [1]

  3. 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 ...

  4. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    Single-cell RNA sequencing (scRNA-Seq) provides the expression profiles of individual cells. Although it is not possible to obtain complete information on every RNA expressed by each cell, due to the small amount of material available, patterns of gene expression can be identified through gene clustering analyses. This can uncover the existence ...

  5. Multiomics - Wikipedia

    en.wikipedia.org/wiki/Multiomics

    A branch of the field of multiomics is the analysis of multilevel single-cell data, called single-cell multiomics. [8] [9] This approach gives us an unprecedent resolution to look at multilevel transitions in health and disease at the single cell level. An advantage in relation to bulk analysis is to mitigate confounding factors derived from ...

  6. Sequence analysis - Wikipedia

    en.wikipedia.org/wiki/Sequence_analysis

    Sequence analysis tasks are often non-trivial to resolve and require the use of relatively complex approaches, many of which are the backbone behind many existing sequence analysis tools. Of the many methods used in practice, the most popular include the following: Dynamic programming; Artificial neural network; Hidden Markov model; Support ...

  7. Single-cell transcriptomics - Wikipedia

    en.wikipedia.org/wiki/Single-cell_transcriptomics

    In single-cell analysis input list of genes of interest can be selected based on differentially expressed genes or groups of genes generated from biclustering. The number of genes annotated to a GO term in the input list is normalised against the number of genes annotated to a GO term in the background set of all genes in genome to determine ...

  8. Fantasy football Start 'Em, Sit 'Em: 40 players to start or ...

    www.aol.com/fantasy-football-start-em-sit...

    Week 12 marks the first "Byemageddon” of the NFL season in fantasy football. A season-high six teams have their bye this week: the New York Jets, Atlanta Falcons, Buffalo Bills, Cincinnati ...

  9. CITE-Seq - Wikipedia

    en.wikipedia.org/wiki/CITE-Seq

    Analysis of single-cell sequencing presents many challenges, such as determining the best way to normalize the data. [8] Due to a new level of complications that arise from sequencing of both proteins and transcripts at a single-cell level, the developers of CITE-Seq and their collaborators are maintaining several tools to help with data analysis.