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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]
Detecting differences in gene expression level between two populations is used both single-cell and bulk transcriptomic data. Specialised methods have been designed for single-cell data that considers single cell features such as technical dropouts and shape of the distribution e.g. Bimodal vs. unimodal. [24]
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 cell–cell interactions at the level of an individual cell, as opposed to more ...
The extensible NEXUS file format is widely used in phylogenetics, evolutionary biology, and bioinformatics.It stores information about taxa, morphological character states, DNA and protein sequence alignments, distances, and phylogenetic trees. [1]
TCR-Seq (T-cell Receptor Sequencing) is a method used to identify and track specific T cells and their clones. [1] TCR-Seq utilizes the unique nature of a T-cell receptor (TCR) as a ready-made molecular barcode. [1] This technology can apply to both single cell sequencing technologies and high throughput screens [1]
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.
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 ...
A sequence profiling tool in bioinformatics is a type of software that presents information related to a genetic sequence, gene name, or keyword input. Such tools generally take a query such as a DNA , RNA , or protein sequence or ‘keyword’ and search one or more databases for information related to that sequence.