LEADER 04403nam  2201021z- 450 
001 9910557388703321
005 20231214133703.0
035   $a(CKB)5400000000042011
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76366
035   $a(EXLCZ)995400000000042011
100   $a20202201d2021      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aSingle Cell Analysis
210   $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021
215   $a1 electronic resource (254 p.)
311   $a3-0365-0628-4 
311   $a3-0365-0629-2 
330   $aCells are the most fundamental building block of all living organisms. The investigation of any type of disease mechanism and its progression still remains challenging due to cellular heterogeneity characteristics and physiological state of cells in a given population. The bulk measurement of millions of cells together can provide some general information on cells, but it cannot evolve the cellular heterogeneity and molecular dynamics in a certain cell population. Compared to this bulk or the average measurement of a large number of cells together, single-cell analysis can provide detailed information on each cell, which could assist in developing an understanding of the specific biological context of cells, such as tumor progression or issues around stem cells. Single-cell omics can provide valuable information about functional mutation and a copy number of variations of cells. Information from single-cell investigations can help to produce a better understanding of intracellular interactions and environmental responses of cellular organelles, which can be beneficial for therapeutics development and diagnostics purposes. This Special Issue is inviting articles related to single-cell analysis and its advantages, limitations, and future prospects regarding health benefits.
606   $aResearch & information: general$2bicssc
606   $aBiology, life sciences$2bicssc
610   $asingle-cell RNA sequencing
610   $acholestatic liver injury
610   $ahepatocyte heterogeneity
610   $ainflammation
610   $aliver tissue repair
610   $asingle cell mass cytometry
610   $asingle cell proteomics
610   $anon-small cell lung cancer
610   $athree-dimensional tissue culture
610   $asnRNA-seq
610   $aRNA velocity
610   $acluster analysis
610   $acardiomyocytes
610   $aseurat
610   $acell heterogeneity
610   $asarcoma
610   $asingle-cell analysis
610   $atotal mRNA level
610   $atranscriptome size
610   $aproteomics
610   $aimmunofluorescence
610   $aimmunohistochemistry
610   $aprotein
610   $agenome
610   $abiomedical applications
610   $acommercialization
610   $aprotein characterization
610   $aconventional approaches
610   $amicrofluidic technologies
610   $asingle cell
610   $ainfectious disease
610   $apathophysiology
610   $atherapeutics
610   $adiagnostics
610   $amicrofluidics
610   $asingle-cell cloning
610   $amonoclonal cell lines
610   $asingle-neuron models
610   $amapping
610   $aelectrophysiological recording
610   $aisolation
610   $atherapy
610   $amicro/nanofluidic devices
610   $amicroelectrode array
610   $atransfection
610   $aartificial intelligence
610   $alocalized high-risk prostate cancer
610   $acirculating tumor cells
610   $athree-dimensional (3-D) telomere profiling
610   $alaser microdissection
610   $awhole-exome genome sequencing
610   $asomatic single nucleotide variants
610   $acopy number alterations
610   $aprecision medicine
615  7$aResearch & information: general
615  7$aBiology, life sciences
700   $aSantra$b Tuhin Subhra$4edt$01311916
702   $aTseng$b Fan-Gang$4edt
702   $aSantra$b Tuhin Subhra$4oth
702   $aTseng$b Fan-Gang$4oth
906   $aBOOK
912   $a9910557388703321
996   $aSingle Cell Analysis$93030556
997   $aUNINA