 Connection
Casey Greene to Genomics
This is a "connection" page, showing publications Casey Greene has written about Genomics.
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Connection Strength |
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2.927 |
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Lee AJ, Doing G, Neff SL, Reiter T, Hogan DA, Greene CS. Compendium-Wide Analysis of Pseudomonas aeruginosa Core and Accessory Genes Reveals Transcriptional Patterns across Strains PAO1 and PA14. mSystems. 2023 02 23; 8(1):e0034222.
Score: 0.601
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Hippen AA, Greene CS. Expanding and Remixing the Metadata Landscape. Trends Cancer. 2021 04; 7(4):276-278.
Score: 0.520
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Byrd JB, Greene AC, Prasad DV, Jiang X, Greene CS. Responsible, practical genomic data sharing that accelerates research. Nat Rev Genet. 2020 10; 21(10):615-629.
Score: 0.508
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Greene CS, Troyanskaya OG. Accurate evaluation and analysis of functional genomics data and methods. Ann N Y Acad Sci. 2012 Jul; 1260:95-100.
Score: 0.282
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Banerjee J, Taroni JN, Allaway RJ, Prasad DV, Guinney J, Greene C. Machine learning in rare disease. Nat Methods. 2023 Jun; 20(6):803-814.
Score: 0.155
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Hippen AA, Crawford J, Gardner JR, Greene CS. wenda_gpu: fast domain adaptation for genomic data. Bioinformatics. 2022 11 15; 38(22):5129-5130.
Score: 0.149
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Stein-O'Brien GL, Arora R, Culhane AC, Favorov AV, Garmire LX, Greene CS, Goff LA, Li Y, Ngom A, Ochs MF, Xu Y, Fertig EJ. Enter the Matrix: Factorization Uncovers Knowledge from Omics. Trends Genet. 2018 10; 34(10):790-805.
Score: 0.111
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Greene CS, Himmelstein DS. Genetic Association-Guided Analysis of Gene Networks for the Study of Complex Traits. Circ Cardiovasc Genet. 2016 Apr; 9(2):179-84.
Score: 0.094
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Gonzalez GH, Tahsin T, Goodale BC, Greene AC, Greene CS. Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery. Brief Bioinform. 2016 Jan; 17(1):33-42.
Score: 0.091
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Tan J, Ung M, Cheng C, Greene CS. Unsupervised feature construction and knowledge extraction from genome-wide assays of breast cancer with denoising autoencoders. Pac Symp Biocomput. 2015; 132-43.
Score: 0.087
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Wong AK, Park CY, Greene CS, Bongo LA, Guan Y, Troyanskaya OG. IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks. Nucleic Acids Res. 2012 Jul; 40(Web Server issue):W484-90.
Score: 0.072
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Greene CS, Sinnott-Armstrong NA, Himmelstein DS, Park PJ, Moore JH, Harris BT. Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS. Bioinformatics. 2010 Mar 01; 26(5):694-5.
Score: 0.061
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Greene CS, Himmelstein DS, Nelson HH, Kelsey KT, Williams SM, Andrew AS, Karagas MR, Moore JH. Enabling personal genomics with an explicit test of epistasis. Pac Symp Biocomput. 2010; 327-36.
Score: 0.061
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Wiley LK, Shortt JA, Roberts ER, Lowery J, Kudron E, Lin M, Mayer D, Wilson M, Brunetti TM, Chavan S, Phang TL, Pozdeyev N, Lesny J, Wicks SJ, Moore ET, Morgenstern JL, Roff AN, Shalowitz EL, Stewart A, Williams C, Edelmann MN, Hull M, Patton JT, Axell L, Ku L, Lee YM, Jirikowic J, Tanaka A, Todd E, White S, Peterson B, Hearst E, Zane R, Greene CS, Mathias R, Coors M, Taylor M, Ghosh D, Kahn MG, Brooks IM, Aquilante CL, Kao D, Rafaels N, Crooks KR, Hess S, Barnes KC, Gignoux CR. Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine. Am J Hum Genet. 2024 01 04; 111(1):11-23.
Score: 0.040
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Cousminer DL, Wagley Y, Pippin JA, Elhakeem A, Way GP, Pahl MC, McCormack SE, Chesi A, Mitchell JA, Kindler JM, Baird D, Hartley A, Howe L, Kalkwarf HJ, Lappe JM, Lu S, Leonard ME, Johnson ME, Hakonarson H, Gilsanz V, Shepherd JA, Oberfield SE, Greene CS, Kelly A, Lawlor DA, Voight BF, Wells AD, Zemel BS, Hankenson KD, Grant SFA. Genome-wide association study implicates novel loci and reveals candidate effector genes for longitudinal pediatric bone accrual. Genome Biol. 2021 01 04; 22(1):1.
Score: 0.033
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Rokita JL, Rathi KS, Cardenas MF, Upton KA, Jayaseelan J, Cross KL, Pfeil J, Egolf LE, Way GP, Farrel A, Kendsersky NM, Patel K, Gaonkar KS, Modi A, Berko ER, Lopez G, Vaksman Z, Mayoh C, Nance J, McCoy K, Haber M, Evans K, McCalmont H, Bendak K, B?hm JW, Marshall GM, Tyrrell V, Kalletla K, Braun FK, Qi L, Du Y, Zhang H, Lindsay HB, Zhao S, Shu J, Baxter P, Morton C, Kurmashev D, Zheng S, Chen Y, Bowen J, Bryan AC, Leraas KM, Coppens SE, Doddapaneni H, Momin Z, Zhang W, Sacks GI, Hart LS, Krytska K, Mosse YP, Gatto GJ, Sanchez Y, Greene CS, Diskin SJ, Vaske OM, Haussler D, Gastier-Foster JM, Kolb EA, Gorlick R, Li XN, Reynolds CP, Kurmasheva RT, Houghton PJ, Smith MA, Lock RB, Raman P, Wheeler DA, Maris JM. Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design. Cell Rep. 2019 11 05; 29(6):1675-1689.e9.
Score: 0.030
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Crowell AM, Greene CS, Loros JJ, Dunlap JC. Learning and Imputation for Mass-spec Bias Reduction (LIMBR). Bioinformatics. 2019 05 01; 35(9):1518-1526.
Score: 0.029
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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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