 Connection
Casey Greene to Single-Cell Analysis
This is a "connection" page, showing publications Casey Greene has written about Single-Cell Analysis.
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Connection Strength |
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3.594 |
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Ivich A, Greene CS. Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution. Cell Rep Methods. 2026 Apr 20; 6(4):101346.
Score: 0.737
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Ivich A, Davidson NR, Grieshober L, Li W, Hicks SC, Doherty JA, Greene CS. Missing cell types in single-cell references impact deconvolution of bulk data but are detectable. Genome Biol. 2025 Apr 07; 26(1):86.
Score: 0.689
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Davidson NR, Zhang F, Greene CS. BuDDI: Bulk Deconvolution with Domain Invariance to predict cell-type-specific perturbations from bulk. PLoS Comput Biol. 2025 Jan; 21(1):e1012742.
Score: 0.678
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Hu Q, Greene CS. Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics. Pac Symp Biocomput. 2019; 24:362-373.
Score: 0.446
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Way GP, Greene CS. Bayesian deep learning for single-cell analysis. Nat Methods. 2018 12; 15(12):1009-1010.
Score: 0.444
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Hawkins AG, Shapiro JA, Spielman SJ, Mejia DS, Venkatesh Prasad D, Ichihara N, Yakovets A, Gottlieb AM, Wheeler KG, Bethell CJ, Foltz SM, O'Malley J, Greene CS, Taroni JN. The Single-Cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors. Cell Genom. 2026 Jul 08; 6(7):101283.
Score: 0.187
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Hippen AA, Falco MM, Weber LM, Erkan EP, Zhang K, Doherty JA, Vähärautio A, Greene CS, Hicks SC. miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data. PLoS Comput Biol. 2021 08; 17(8):e1009290.
Score: 0.134
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Lê Cao KA, Abadi AJ, Davis-Marcisak EF, Hsu L, Arora A, Coullomb A, Deshpande A, Feng Y, Jeganathan P, Loth M, Meng C, Mu W, Pancaldi V, Sankaran K, Righelli D, Singh A, Sodicoff JS, Stein-O'Brien GL, Subramanian A, Welch JD, You Y, Argelaguet R, Carey VJ, Dries R, Greene CS, Holmes S, Love MI, Ritchie ME, Yuan GC, Culhane AC, Fertig E. Community-wide hackathons to identify central themes in single-cell multi-omics. Genome Biol. 2021 08 05; 22(1):220.
Score: 0.134
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Taylor DM, Aronow BJ, Tan K, Bernt K, Salomonis N, Greene CS, Frolova A, Henrickson SE, Wells A, Pei L, Jaiswal JK, Whitsett J, Hamilton KE, MacParland SA, Kelsen J, Heuckeroth RO, Potter SS, Vella LA, Terry NA, Ghanem LR, Kennedy BC, Helbig I, Sullivan KE, Castelo-Soccio L, Kreigstein A, Herse F, Nawijn MC, Koppelman GH, Haendel M, Harris NL, Rokita JL, Zhang Y, Regev A, Rozenblatt-Rosen O, Rood JE, Tickle TL, Vento-Tormo R, Alimohamed S, Lek M, Mar JC, Loomes KM, Barrett DM, Uapinyoying P, Beggs AH, Agrawal PB, Chen YW, Muir AB, Garmire LX, Snapper SB, Nazarian J, Seeholzer SH, Fazelinia H, Singh LN, Faryabi RB, Raman P, Dawany N, Xie HM, Devkota B, Diskin SJ, Anderson SA, Rappaport EF, Peranteau W, Wikenheiser-Brokamp KA, Teichmann S, Wallace D, Peng T, Ding YY, Kim MS, Xing Y, Kong SW, Bönnemann CG, Mandl KD, White PS. The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution. Dev Cell. 2019 04 08; 49(1):10-29.
Score: 0.113
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Dang MT, Gonzalez MV, Gaonkar KS, Rathi KS, Young P, Arif S, Zhai L, Alam Z, Devalaraja S, To TKJ, Folkert IW, Raman P, Rokita JL, Martinez D, Taroni JN, Shapiro JA, Greene CS, Savonen C, Mafra F, Hakonarson H, Curran T, Haldar M. Macrophages in SHH subgroup medulloblastoma display dynamic heterogeneity that varies with treatment modality. Cell Rep. 2021 03 30; 34(13):108917.
Score: 0.033
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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