-
1
-
-
84896714251
-
Transcriptional mechanisms of cell fate decisions revealed by single cell expression profiling
-
Moignard V, Gottgens B. Transcriptional mechanisms of cell fate decisions revealed by single cell expression profiling. Bioessays 2014; 36: 419-426.
-
(2014)
Bioessays
, vol.36
, pp. 419-426
-
-
Moignard, V.1
Gottgens, B.2
-
2
-
-
83255177150
-
Single-cell dissection of transcriptional heterogeneity in human colon tumors
-
Dalerba P, Kalisky T, Sahoo D, Rajendran PS, Rothenberg ME, Leyrat AA, et al. Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nat Biotechnol 2011; 29: 1120-1127.
-
(2011)
Nat Biotechnol
, vol.29
, pp. 1120-1127
-
-
Dalerba, P.1
Kalisky, T.2
Sahoo, D.3
Rajendran, P.S.4
Rothenberg, M.E.5
Leyrat, A.A.6
-
3
-
-
84866369892
-
Single-cell expression analyses during cellular reprogramming reveal an early stochastic and a late hierarchic phase
-
Buganim Y, Faddah DA, Cheng AW, Itskovich E, Markoulaki S, Ganz K, et al.. Single-cell expression analyses during cellular reprogramming reveal an early stochastic and a late hierarchic phase. Cell 2012; 150: 1209-1222.
-
(2012)
Cell
, vol.150
, pp. 1209-1222
-
-
Buganim, Y.1
Faddah, D.A.2
Cheng, A.W.3
Itskovich, E.4
Markoulaki, S.5
Ganz, K.6
-
4
-
-
84876471008
-
Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis
-
Moignard V, Macaulay IC, Swiers G, Buettner F, Schütte J, Calero-Nieto FJ, et al. Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis. Nat Cell Biol 2013; 15: 363-372.
-
(2013)
Nat Cell Biol
, vol.15
, pp. 363-372
-
-
Moignard, V.1
Macaulay, I.C.2
Swiers, G.3
Buettner, F.4
Schütte, J.5
Calero-Nieto, F.J.6
-
5
-
-
84880280631
-
ViSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
-
Amir ED, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol 2013; 31: 545-552.
-
(2013)
Nat Biotechnol
, vol.31
, pp. 545-552
-
-
Amir, E.D.1
Davis, K.L.2
Tadmor, M.D.3
Simonds, E.F.4
Levine, J.H.5
Bendall, S.C.6
-
6
-
-
84940446838
-
Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations
-
Wilson NK, Kent DG, Buettner F, Shehata M, Macaulay IC, Calero-Nieto F, et al. Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations. Cell Stem Cell 2015; 16: 712-724.
-
(2015)
Cell Stem Cell
, vol.16
, pp. 712-724
-
-
Wilson, N.K.1
Kent, D.G.2
Buettner, F.3
Shehata, M.4
Macaulay, I.C.5
Calero-Nieto, F.6
-
7
-
-
84893905629
-
Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types
-
Jaitin DA, Kenigsberg E, Keren-Shaul H, Elefant N, Paul F, Zaretsky I, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 2014; 343: 776-779.
-
(2014)
Science
, vol.343
, pp. 776-779
-
-
Jaitin, D.A.1
Kenigsberg, E.2
Keren-Shaul, H.3
Elefant, N.4
Paul, F.5
Zaretsky, I.6
-
8
-
-
84941201582
-
Single-cell messenger RNA sequencing reveals rare intestinal cell types
-
Grün D, Lyubimova A, Kester L, Wiebrands K, Basak O, Sasaki N, et al. Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 2015; 525: 251-255.
-
(2015)
Nature
, vol.525
, pp. 251-255
-
-
Grün, D.1
Lyubimova, A.2
Kester, L.3
Wiebrands, K.4
Basak, O.5
Sasaki, N.6
-
9
-
-
84901188210
-
Sequencing reveals T helper cells synthesizing steroids de Novo to contribute to immune homeostasis
-
Mahata B, Zhang X, Kolodziejczyk AA, Proserpio V, Haim-Vilmovsky L, Taylor AE, et al. Sequencing Reveals T Helper Cells Synthesizing Steroids De Novo to Contribute to Immune Homeostasis. Cell Rep 2014; 7: 1130-1142.
-
(2014)
Cell Rep
, vol.7
, pp. 1130-1142
-
-
Mahata, B.1
Zhang, X.2
Kolodziejczyk, A.A.3
Proserpio, V.4
Haim-Vilmovsky, L.5
Taylor, A.E.6
-
10
-
-
84902668801
-
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
-
Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 2014; 344: 1396-1401.
-
(2014)
Science
, vol.344
, pp. 1396-1401
-
-
Patel, A.P.1
Tirosh, I.2
Trombetta, J.J.3
Shalek, A.K.4
Gillespie, S.M.5
Wakimoto, H.6
-
11
-
-
84903185013
-
Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
-
Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 2014; 510: 363-369.
-
(2014)
Nature
, vol.510
, pp. 363-369
-
-
Shalek, A.K.1
Satija, R.2
Shuga, J.3
Trombetta, J.J.4
Gennert, D.5
Lu, D.6
-
12
-
-
84937604921
-
An interactive reference framework for modeling a dynamic immune system
-
Spitzer MH, Gherardini PF, Fragiadakis GK, Bhattacharya N, Yuan RT, Hotson AN, et al. An interactive reference framework for modeling a dynamic immune system. Science 2015; 349: 1259425.
-
(2015)
Science
, vol.349
, pp. 1259425
-
-
Spitzer, M.H.1
Gherardini, P.F.2
Fragiadakis, G.K.3
Bhattacharya, N.4
Yuan, R.T.5
Hotson, A.N.6
-
13
-
-
84900873950
-
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
-
Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 2014; 32: 381-386.
-
(2014)
Nat Biotechnol
, vol.32
, pp. 381-386
-
-
Trapnell, C.1
Cacchiarelli, D.2
Grimsby, J.3
Pokharel, P.4
Li, S.5
Morse, M.6
-
14
-
-
84899574465
-
Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development
-
Bendall SC, Davis KL, Amir ED, Tadmor MD, Simonds EF, Tiffany JC, et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 2014; 157: 714-725.
-
(2014)
Cell
, vol.157
, pp. 714-725
-
-
Bendall, S.C.1
Davis, K.L.2
Amir, E.D.3
Tadmor, M.D.4
Simonds, E.F.5
Tiffany, J.C.6
-
15
-
-
84924353105
-
Decoding the regulatory network of early blood development from single-cell gene expression measurements
-
Moignard V, Woodhouse S, Haghverdi L, Lilly AJ, Tanaka Y, Wilkinson AC, et al. Decoding the regulatory network of early blood development from single-cell gene expression measurements. Nat Biotechnol 2015; 33: 269-276.
-
(2015)
Nat Biotechnol
, vol.33
, pp. 269-276
-
-
Moignard, V.1
Woodhouse, S.2
Haghverdi, L.3
Lilly, A.J.4
Tanaka, Y.5
Wilkinson, A.C.6
-
16
-
-
84872195205
-
Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
-
Livak KJ, Wills QF, Tipping AJ, Datta K, Mittal R, Goldson AJ, et al. Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells. Methods 2013; 59: 71-79.
-
(2013)
Methods
, vol.59
, pp. 71-79
-
-
Livak, K.J.1
Wills, Q.F.2
Tipping, A.J.3
Datta, K.4
Mittal, R.5
Goldson, A.J.6
-
17
-
-
84869095801
-
Nanogdependent feedback loops regulate murine embryonic stem cell heterogeneity
-
MacArthur BD, Sevilla A, Lenz M, Müller FJ, Schuldt BM, Schuppert AA, et al. Nanogdependent feedback loops regulate murine embryonic stem cell heterogeneity. Nat Cell Biol 2012; 14: 1139-1147.
-
(2012)
Nat Cell Biol
, vol.14
, pp. 1139-1147
-
-
MacArthur, B.D.1
Sevilla, A.2
Lenz, M.3
Müller, F.J.4
Schuldt, B.M.5
Schuppert, A.A.6
-
18
-
-
84862778068
-
Inferring rules of lineage commitment in haematopoiesis
-
Pina C, Fugazza C, Tipping AJ, Brown J, Soneji S, Teles J, et al. Inferring rules of lineage commitment in haematopoiesis. Nat Cell Biol 2012; 14: 287-294.
-
(2012)
Nat Cell Biol
, vol.14
, pp. 287-294
-
-
Pina, C.1
Fugazza, C.2
Tipping, A.J.3
Brown, J.4
Soneji, S.5
Teles, J.6
-
20
-
-
77951912210
-
Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst
-
Guo G, Huss M, Tong GQ, Wang C, Li Sun L, Clarke ND, et al. Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst. Dev Cell 2010; 18: 675-685.
-
(2010)
Dev Cell
, vol.18
, pp. 675-685
-
-
Guo, G.1
Huss, M.2
Tong, G.Q.3
Wang, C.4
Li Sun, L.5
Clarke, N.D.6
-
21
-
-
84890649933
-
Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level
-
Swiers G, Baumann C, ORourke J, Giannoulatou E, Taylor S, Joshi A, et al. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level. Nat Commun 2013; 4: 2924.
-
(2013)
Nat Commun
, vol.4
, pp. 2924
-
-
Swiers, G.1
Baumann, C.2
Orourke, J.3
Giannoulatou, E.4
Taylor, S.5
Joshi, A.6
-
22
-
-
84885172419
-
Mapping cellular hierarchy by single-cell analysis of the cell surface repertoire
-
Guo G, Luc S, Marco E, Lin TW, Peng C, Kerenyi MA, et al. Mapping cellular hierarchy by single-cell analysis of the cell surface repertoire. Cell Stem Cell 2013; 13: 492-505.
-
(2013)
Cell Stem Cell
, vol.13
, pp. 492-505
-
-
Guo, G.1
Luc, S.2
Marco, E.3
Lin, T.W.4
Peng, C.5
Kerenyi, M.A.6
-
23
-
-
79952323055
-
Defining cell populations with single-cell gene expression profiling: Correlations and identification of astrocyte subpopulations
-
StAhlberg A, Andersson D, Aurelius J, Faiz M, Pekna M, Kubista M, et al. Defining cell populations with single-cell gene expression profiling: correlations and identification of astrocyte subpopulations. Nucleic Acids Res 2011; 39: e24.
-
(2011)
Nucleic Acids Res
, vol.39
, pp. e24
-
-
StAhlberg, A.1
Andersson, D.2
Aurelius, J.3
Faiz, M.4
Pekna, M.5
Kubista, M.6
-
24
-
-
84896739948
-
Single cell genomics: Advances and future perspectives
-
Macaulay IC, Voet T. Single cell genomics: advances and future perspectives. PLoS Genet 2014; 10: e1004126.
-
(2014)
PLoS Genet
, vol.10
, pp. e1004126
-
-
Macaulay, I.C.1
Voet, T.2
-
25
-
-
84923647450
-
Computational and analytical challenges in singlecell transcriptomics
-
Stegle O, Teichmann SA, Marioni JC. Computational and analytical challenges in singlecell transcriptomics. Nat Rev Genet 2015; 16: 133-145.
-
(2015)
Nat Rev Genet
, vol.16
, pp. 133-145
-
-
Stegle, O.1
Teichmann, S.A.2
Marioni, J.C.3
-
26
-
-
84866953427
-
CEL-Seq: Single-cell RNA-Seq by multiplexed linear amplification
-
Hashimshony T, Wagner F, Sher N, Yanai I. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep 2012; 2: 666-673.
-
(2012)
Cell Rep
, vol.2
, pp. 666-673
-
-
Hashimshony, T.1
Wagner, F.2
Sher, N.3
Yanai, I.4
-
27
-
-
79959403670
-
Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq
-
Islam S, Kjallquist U, Moliner A, Zajac P, Fan JB, Lonnerberg P, et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res 2011; 21: 1160-1167.
-
(2011)
Genome Res
, vol.21
, pp. 1160-1167
-
-
Islam, S.1
Kjallquist, U.2
Moliner, A.3
Zajac, P.4
Fan, J.B.5
Lonnerberg, P.6
-
28
-
-
84887101406
-
Smart-seq2 for sensitive full-length transcriptome profiling in single cells
-
Picelli S, Bjorklund AK, Faridani OR, Sagasser S, Winberg G, Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 2013; 10: 1096-1098.
-
(2013)
Nat Methods
, vol.10
, pp. 1096-1098
-
-
Picelli, S.1
Bjorklund, A.K.2
Faridani, O.R.3
Sagasser, S.4
Winberg, G.5
Sandberg, R.6
-
29
-
-
67349146589
-
MRNA-Seq whole-transcriptome analysis of a single cell
-
Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 2009; 6: 377-382.
-
(2009)
Nat Methods
, vol.6
, pp. 377-382
-
-
Tang, F.1
Barbacioru, C.2
Wang, Y.3
Nordman, E.4
Lee, C.5
Xu, N.6
-
30
-
-
84856484968
-
Counting absolute numbers of molecules using unique molecular identifiers
-
Kivioja T, Vaharautio A, Karlsson K, Bonke M, Enge M, Linnarsson S, et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat Methods 2012; 9: 72-74.
-
(2012)
Nat Methods
, vol.9
, pp. 72-74
-
-
Kivioja, T.1
Vaharautio, A.2
Karlsson, K.3
Bonke, M.4
Enge, M.5
Linnarsson, S.6
-
31
-
-
80052521697
-
Synthetic spike-in standards for RNA-seq experiments
-
Jiang L, Schlesinger F, Davis CA, Zhang Y, Li R, Salit M, et al. Synthetic spike-in standards for RNA-seq experiments. Genome Res 2011; 21: 1543-1551.
-
(2011)
Genome Res
, vol.21
, pp. 1543-1551
-
-
Jiang, L.1
Schlesinger, F.2
Davis, C.A.3
Zhang, Y.4
Li, R.5
Salit, M.6
-
32
-
-
84895069488
-
Quantitative single-cell RNA-seq with unique molecular identifiers
-
Islam S, Zeisel A, Joost S, La Manno G, Zajac P, Kasper M, et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat Methods 2014; 11: 163-166.
-
(2014)
Nat Methods
, vol.11
, pp. 163-166
-
-
Islam, S.1
Zeisel, A.2
Joost, S.3
La Manno, G.4
Zajac, P.5
Kasper, M.6
-
33
-
-
65449136284
-
TopHat: Discovering splice junctions with RNA-Seq
-
Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 2009; 25: 1105-1111.
-
(2009)
Bioinformatics
, vol.25
, pp. 1105-1111
-
-
Trapnell, C.1
Pachter, L.2
Salzberg, S.L.3
-
34
-
-
84871809302
-
STAR: Ultrafast universal RNA-seq aligner
-
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013; 29: 15-21.
-
(2013)
Bioinformatics
, vol.29
, pp. 15-21
-
-
Dobin, A.1
Davis, C.A.2
Schlesinger, F.3
Drenkow, J.4
Zaleski, C.5
Jha, S.6
-
35
-
-
77951820899
-
Fast and SNP-tolerant detection of complex variants and splicing in short reads
-
Wu TD, Nacu S. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 2010; 26: 873-881.
-
(2010)
Bioinformatics
, vol.26
, pp. 873-881
-
-
Wu, T.D.1
Nacu, S.2
-
36
-
-
84928987900
-
HTSeq - A Python framework to work with high-throughput sequencing data
-
Anders S, Pyl PT, Huber W. HTSeq - A Python framework to work with high-throughput sequencing data. Bioinformatics 2015; 31: 166-169.
-
(2015)
Bioinformatics
, vol.31
, pp. 166-169
-
-
Anders, S.1
Pyl, P.T.2
Huber, W.3
-
37
-
-
0003684449
-
-
2nd edn. Springer: Berlin, Germany
-
Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning: Data Mining, Inference and Prediction 2nd edn. Springer: Berlin, Germany, 2011.
-
(2011)
The Elements of Statistical Learning: Data Mining, Inference and Prediction
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
40
-
-
85170282443
-
A density-based algorithm for discovering clusters in large spatial databases with noise
-
Institute for Computer Science, University of Munich: München, Germany
-
Ester M, Kriegel HP, Sander J, Xu X. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining (KDD-96); 226-231. Institute for Computer Science, University of Munich: München, Germany, 1996.
-
(1996)
Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining (KDD-96)
, pp. 226-231
-
-
Ester, M.1
Kriegel, H.P.2
Sander, J.3
Xu, X.4
-
42
-
-
80054768631
-
Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
-
Qiu P, Simonds EF, Bendall SC, Gibbs KD, Bruggner RV, Linderman MD, et al. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat Biotechnol 2011; 29: 886-891.
-
(2011)
Nat Biotechnol
, vol.29
, pp. 886-891
-
-
Qiu, P.1
Simonds, E.F.2
Bendall, S.C.3
Gibbs, K.D.4
Bruggner, R.V.5
Linderman, M.D.6
-
43
-
-
84924565530
-
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
-
Zeisel A, Muoz-Manchado AB, Codeluppi S, Lonnerberg P, La Manno G, Jureus A, et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 2015; 347: 1138-1142.
-
(2015)
Science
, vol.347
, pp. 1138-1142
-
-
Zeisel, A.1
Muoz-Manchado, A.B.2
Codeluppi, S.3
Lonnerberg, P.4
La Manno, G.5
Jureus, A.6
-
44
-
-
84941201582
-
Single-cell messenger RNA sequencing reveals rare intestinal cell types
-
Grün D, Lyubimova A, Kester L, Wiebrands K, Basak O, Sasaki N, et al. Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 2015; 525: 251-255.
-
(2015)
Nature
, vol.525
, pp. 251-255
-
-
Grün, D.1
Lyubimova, A.2
Kester, L.3
Wiebrands, K.4
Basak, O.5
Sasaki, N.6
-
45
-
-
84923188586
-
Deconstructing transcriptional heterogeneity in pluripotent stem cells
-
Kumar RM, Cahan P, Shalek AK, Satija R, DaleyKeyser AJ, Li H, et al. Deconstructing transcriptional heterogeneity in pluripotent stem cells. Nature 2014; 516: 56-61.
-
(2014)
Nature
, vol.516
, pp. 56-61
-
-
Kumar, R.M.1
Cahan, P.2
Shalek, A.K.3
Satija, R.4
DaleyKeyser, A.J.5
Li, H.6
-
47
-
-
0347243182
-
Nonlinear component analysis as a kernel eigenvalue problem
-
Scholkopf B, Smola A, Müller KR. Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput 1998; 10: 1299-1319.
-
(1998)
Neural Comput
, vol.10
, pp. 1299-1319
-
-
Scholkopf, B.1
Smola, A.2
Müller, K.R.3
-
49
-
-
19644394100
-
Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
-
Coifman RR, Lafon S, Lee AB, Maggioni M, Nadler B, Warner F, et al. Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps. Proc Natl Acad Sci USA 2005; 102: 7426-7431.
-
(2005)
Proc Natl Acad Sci USA
, vol.102
, pp. 7426-7431
-
-
Coifman, R.R.1
Lafon, S.2
Lee, A.B.3
Maggioni, M.4
Nadler, B.5
Warner, F.6
-
50
-
-
77952984416
-
Diffusion maps - A probabilistic interpretation for spectral embedding and clustering algorithms
-
Gorban AN, Kegl B, Wunsch DC, Zinovyev A (eds) Springer: Berlin, Germany
-
Nadler B, Lafon S, Coifman R, Kevrekidis IG. Diffusion maps - a probabilistic interpretation for spectral embedding and clustering algorithms. In: Gorban AN, Kegl B, Wunsch DC, Zinovyev A (eds). Principal Manifolds for Data Visualization and Dimension Reduction. Springer: Berlin, Germany, 2008; pp 238-260.
-
(2008)
Principal Manifolds for Data Visualization and Dimension Reduction
, pp. 238-260
-
-
Nadler, B.1
Lafon, S.2
Coifman, R.3
Kevrekidis, I.G.4
-
51
-
-
33847047461
-
Epigenetics: A landscape takes shape
-
Goldberg AD, Allis CD, Bernstein E. Epigenetics: a landscape takes shape. Cell 2007; 128: 635-638.
-
(2007)
Cell
, vol.128
, pp. 635-638
-
-
Goldberg, A.D.1
Allis, C.D.2
Bernstein, E.3
-
52
-
-
84919775831
-
Accelerating t-SNE using Tree-Based Algorithms
-
van der Maaten LPJ. Accelerating t-SNE using Tree-Based Algorithms. J Mach Learn Res 2014; 15: 3221-3245.
-
(2014)
J Mach Learn Res
, vol.15
, pp. 3221-3245
-
-
Van Der Maaten, L.P.J.1
-
53
-
-
84941753288
-
Diffusion maps for high-dimensional single-cell analysis of differentiation data
-
Haghverdi L, Buettner F, Theis FJ. Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics 2015; 31: 2989-2998.
-
(2015)
Bioinformatics
, vol.31
, pp. 2989-2998
-
-
Haghverdi, L.1
Buettner, F.2
Theis, F.J.3
-
54
-
-
84961834762
-
A geometric viewpoint of manifold learning
-
Lin B, He X, Ye J. A geometric viewpoint of manifold learning. Appl Inform 2015; 2: 3.
-
(2015)
Appl Inform
, vol.2
, pp. 3
-
-
Lin, B.1
He, X.2
Ye, J.3
-
55
-
-
84934442835
-
Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis
-
Levine JH, Simonds EF, Bendall SC, Davis KL, Amir ED, Tadmor MD, et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell 2015; 162: 184-197.
-
(2015)
Cell
, vol.162
, pp. 184-197
-
-
Levine, J.H.1
Simonds, E.F.2
Bendall, S.C.3
Davis, K.L.4
Amir, E.D.5
Tadmor, M.D.6
-
56
-
-
33646351332
-
Relevance networks: A first step toward finding genetic regulatory networks within microarray data
-
Parmigiani G, Garett ES, Irizarry RA, Zeger SL (eds) Springer: Berlin, Germany
-
Butte AJ, Kohane IS. Relevance networks: a first step toward finding genetic regulatory networks within microarray data. In: Parmigiani G, Garett ES, Irizarry RA, Zeger SL (eds).The Analysis of Gene Expression Data. Springer: Berlin, Germany, 2003; pp 1-45.
-
(2003)
The Analysis of Gene Expression Data
, pp. 1-45
-
-
Butte, A.J.1
Kohane, I.S.2
-
57
-
-
84937641068
-
Single-cell network analysis identifies DDIT3 as a nodal lineage regulator in hematopoiesis
-
Pina C, Teles J, Fugazza C, May G, Wang D, Guo Y, et al. Single-cell network analysis identifies DDIT3 as a nodal lineage regulator in hematopoiesis. Cell Rep 2015; 11: 1503-1510.
-
(2015)
Cell Rep
, vol.11
, pp. 1503-1510
-
-
Pina, C.1
Teles, J.2
Fugazza, C.3
May, G.4
Wang, D.5
Guo, Y.6
-
58
-
-
77958570788
-
Inferring regulatory networks from expression data using tree-based methods
-
Huynh-Thu VA, Irrthum A, Wehenkel L, Geurts P. Inferring regulatory networks from expression data using tree-based methods. PLoS ONE 2010; 5: e12776.
-
(2010)
PLoS ONE
, vol.5
, pp. e12776
-
-
Huynh-Thu, V.A.1
Irrthum, A.2
Wehenkel, L.3
Geurts, P.4
-
59
-
-
84870305264
-
Wisdom of crowds for robust gene network inference
-
The DREAM5 Consortium et al
-
Marbach D, Costello JC, Küffner R, Vega NM, Prill RJ, Camacho DM. The DREAM5 Consortium, et al. Wisdom of crowds for robust gene network inference. Nat Methods 2012; 9: 796-804.
-
(2012)
Nat Methods
, vol.9
, pp. 796-804
-
-
Marbach, D.1
Costello, J.C.2
Küffner, R.3
Vega, N.M.4
Prill, R.J.5
Camacho, D.M.6
-
60
-
-
84931084251
-
Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data
-
Ocone A, Haghverdi L, Mueller NS, Theis FJ. Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data. Bioinformatics 2015; 31: i89-i96.
-
(2015)
Bioinformatics
, vol.31
, pp. i89-i96
-
-
Ocone, A.1
Haghverdi, L.2
Mueller, N.S.3
Theis, F.J.4
-
61
-
-
84914127300
-
Conditional Density-based Analysis of T cell Signaling in Single Cell Data
-
Krishnaswamy S, Spitzer M, Mingueneau M, Bendall SC, Stone EL, Litvin O, et al. Conditional Density-based Analysis of T cell Signaling in Single Cell Data. Science 2014; 346: 1250689.
-
(2014)
Science
, vol.346
, pp. 1250689
-
-
Krishnaswamy, S.1
Spitzer, M.2
Mingueneau, M.3
Bendall, S.C.4
Stone, E.L.5
Litvin, O.6
-
64
-
-
17644427718
-
Causal protein-signaling networks derived from multiparameter single-cell data
-
Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP. Causal protein-signaling networks derived from multiparameter single-cell data. Science 2005; 308: 523-529.
-
(2005)
Science
, vol.308
, pp. 523-529
-
-
Sachs, K.1
Perez, O.2
Pe'Er, D.3
Lauffenburger, D.A.4
Nolan, G.P.5
-
65
-
-
84951188597
-
Synthesising executable gene regulatory networks from single-cell gene expression data
-
Springer
-
Fisher J, Koksal AS, Piterman N, Woodhouse S. Synthesising Executable Gene Regulatory Networks from Single-Cell Gene Expression Data, 27th International Conference on Computer Aided Verification, Vol. 9206 of Lecture Notes in Computer Science, Springer, 2015.
-
(2015)
27th International Conference on Computer Aided Verification, Vol. 9206 of Lecture Notes in Computer Science
-
-
Fisher, J.1
Koksal, A.S.2
Piterman, N.3
Woodhouse, S.4
-
67
-
-
84897090228
-
Highly multiplexed subcellular RNA sequencing in situ
-
Lee JH, Daugharthy ER, Scheiman J, Kalhor R, Yang JL, Ferrante TC, et al. Highly multiplexed subcellular RNA sequencing in situ. Science 2014; 343: 1360-1363.
-
(2014)
Science
, vol.343
, pp. 1360-1363
-
-
Lee, J.H.1
Daugharthy, E.R.2
Scheiman, J.3
Kalhor, R.4
Yang, J.L.5
Ferrante, T.C.6
-
68
-
-
84929151009
-
Spatial reconstruction of single-cell gene expression data
-
Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol 2015; 33: 495-502.
-
(2015)
Nat Biotechnol
, vol.33
, pp. 495-502
-
-
Satija, R.1
Farrell, J.A.2
Gennert, D.3
Schier, A.F.4
Regev, A.5
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