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Prediction of Gene Activity in Early B Cell Development Based on an Integrative Multi-Omics Analysis.

Journal of proteomics & bioinformatics

Heydarian M, Luperchio TR, Cutler J, Mitchell CJ, Kim MS, Pandey A, Sollner-Webb B, Reddy K.
PMID: 25544807
J Proteomics Bioinform. 2014 Feb 17;7. doi: 10.4172/jpb.1000302.

An increasingly common method for predicting gene activity is genome-wide chromatin immuno-precipitation of 'active' chromatin modifications followed by massively parallel sequencing (ChIP-seq). In order to understand better the relationship between developmentally regulated chromatin landscapes and regulation of early B...

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Heydarian M, Luperchio TR, Cutler J, et al. Prediction of Gene Activity in Early B Cell Development Based on an Integrative Multi-Omics Analysis. J Proteomics Bioinform. 2014;7doi: 10.4172/jpb.1000302.
Heydarian, M., Luperchio, T. R., Cutler, J., Mitchell, C. J., Kim, M. S., Pandey, A., Sollner-Webb, B., & Reddy, K. (2014). Prediction of Gene Activity in Early B Cell Development Based on an Integrative Multi-Omics Analysis. Journal of proteomics & bioinformatics, 7. https://doi.org/10.4172/jpb.1000302
Heydarian, Mohammad, et al. "Prediction of Gene Activity in Early B Cell Development Based on an Integrative Multi-Omics Analysis." Journal of proteomics & bioinformatics vol. 7 (2014). doi: https://doi.org/10.4172/jpb.1000302
Heydarian M, Luperchio TR, Cutler J, Mitchell CJ, Kim MS, Pandey A, Sollner-Webb B, Reddy K. Prediction of Gene Activity in Early B Cell Development Based on an Integrative Multi-Omics Analysis. J Proteomics Bioinform. 2014 Feb 17;7. doi: 10.4172/jpb.1000302. PMID: 25544807; PMCID: PMC4276347.
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Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism.

Nature communications

Gupta S, Ellis SE, Ashar FN, Moes A, Bader JS, Zhan J, West AB, Arking DE.
PMID: 25494366
Nat Commun. 2014 Dec 10;5:5748. doi: 10.1038/ncomms6748.

Recent studies of genomic variation associated with autism have suggested the existence of extreme heterogeneity. Large-scale transcriptomics should complement these results to identify core molecular pathways underlying autism. Here we report results from a large-scale RNA sequencing effort, utilizing...

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Gupta S, Ellis SE, Ashar FN, et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat Commun. 2014;5:5748doi: 10.1038/ncomms6748.
Gupta, S., Ellis, S. E., Ashar, F. N., Moes, A., Bader, J. S., Zhan, J., West, A. B., & Arking, D. E. (2014). Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nature communications, 55748. https://doi.org/10.1038/ncomms6748
Gupta, Simone, et al. "Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism." Nature communications vol. 5 (2014): 5748. doi: https://doi.org/10.1038/ncomms6748
Gupta S, Ellis SE, Ashar FN, Moes A, Bader JS, Zhan J, West AB, Arking DE. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat Commun. 2014 Dec 10;5:5748. doi: 10.1038/ncomms6748. PMID: 25494366; PMCID: PMC4270294.
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Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Hypertension (Dallas, Tex. : 1979)

Wain LV, Vaez A, Jansen R, Joehanes R, van der Most PJ, Erzurumluoglu AM, O'Reilly PF, Cabrera CP, Warren HR, Rose LM, Verwoert GC, Hottenga JJ, Strawbridge RJ, Esko T, Arking DE, Hwang SJ, Guo X, Kutalik Z, Trompet S, Shrine N, Teumer A, Ried JS, Bis JC, Smith AV, Amin N, Nolte IM, Lyytikäinen LP, Mahajan A, Wareham NJ, Hofer E, Joshi PK, Kristiansson K, Traglia M, Havulinna AS, Goel A, Nalls MA, Sõber S, Vuckovic D, Luan J, Del Greco M F, Ayers KL, Marrugat J, Ruggiero D, Lopez LM, Niiranen T, Enroth S, Jackson AU, Nelson CP, Huffman JE, Zhang W, Marten J, Gandin I, Harris SE, Zemunik T, Lu Y, Evangelou E, Shah N, de Borst MH, Mangino M, Prins BP, Campbell A, Li-Gao R, Chauhan G, Oldmeadow C, Abecasis G, Abedi M, Barbieri CM, Barnes MR, Batini C, Beilby J, Blake T, Boehnke M, Bottinger EP, Braund PS, Brown M, Brumat M, Campbell H, Chambers JC, Cocca M, Collins F, Connell J, Cordell HJ, Damman JJ, Davies G, de Geus EJ, de Mutsert R, Deelen J, Demirkale Y, Doney ASF, Dörr M, Farrall M, Ferreira T, Frånberg M, Gao H, Giedraitis V, Gieger C, Giulianini F, Gow AJ, Hamsten A, Harris TB, Hofman A, Holliday EG, Hui J, Jarvelin MR, Johansson Å, Johnson AD, Jousilahti P, Jula A, Kähönen M, Kathiresan S, Khaw KT, Kolcic I, Koskinen S, Langenberg C, Larson M, Launer LJ, Lehne B, Liewald DCM, Lin L, Lind L, Mach F, Mamasoula C, Menni C, Mifsud B, Milaneschi Y, Morgan A, Morris AD, Morrison AC, Munson PJ, Nandakumar P, Nguyen QT, Nutile T, Oldehinkel AJ, Oostra BA, Org E, Padmanabhan S, Palotie A, Paré G, Pattie A, Penninx BWJH, Poulter N, Pramstaller PP, Raitakari OT, Ren M, Rice K, Ridker PM, Riese H, Ripatti S, Robino A, Rotter JI, Rudan I, Saba Y, Saint Pierre A, Sala CF, Sarin AP, Schmidt R, Scott R, Seelen MA, Shields DC, Siscovick D, Sorice R, Stanton A, Stott DJ, Sundström J, Swertz M, Taylor KD, Thom S, Tzoulaki I, Tzourio C, Uitterlinden AG, Völker U, Vollenweider P, Wild S, Willemsen G, Wright AF, Yao J, Thériault S, Conen D, Attia J, Sever P, Debette S, Mook-Kanamori DO, Zeggini E, Spector TD, van der Harst P, Palmer CNA, Vergnaud AC, Loos RJF, Polasek O, Starr JM, Girotto G, Hayward C, Kooner JS, Lindgren CM, Vitart V, Samani NJ, Tuomilehto J, Gyllensten U, Knekt P, Deary IJ, Ciullo M, Elosua R, Keavney BD, Hicks AA, Scott RA, Gasparini P, Laan M, Liu Y, Watkins H, Hartman CA, Salomaa V, Toniolo D, Perola M, Wilson JF, Schmidt H, Zhao JH, Lehtimäki T, van Duijn CM, Gudnason V, Psaty BM, Peters A, Rettig R, James A, Jukema JW, Strachan DP, Palmas W, Metspalu A, Ingelsson E, Boomsma DI, Franco OH, Bochud M, Newton-Cheh C, Munroe PB, Elliott P, Chasman DI, Chakravarti A, Knight J, Morris AP, Levy D, Tobin MD, Snieder H, Caulfield MJ, Ehret GB.
PMID: 28739976
Hypertension. 2017 Jul 24; doi: 10.1161/HYPERTENSIONAHA.117.09438. Epub 2017 Jul 24.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel...

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Wain LV, Vaez A, Jansen R, et al. Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney. Hypertension. 2017;doi: 10.1161/HYPERTENSIONAHA.117.09438.
Wain, L. V., Vaez, A., Jansen, R., Joehanes, R., van der Most, P. J., Erzurumluoglu, A. M., O'Reilly, P. F., Cabrera, C. P., Warren, H. R., Rose, L. M., Verwoert, G. C., Hottenga, J. J., Strawbridge, R. J., Esko, T., Arking, D. E., Hwang, S. J., Guo, X., Kutalik, Z., Trompet, S., Shrine, N., Teumer, A., Ried, J. S., Bis, J. C., Smith, A. V., Amin, N., Nolte, I. M., Lyytikäinen, L. P., Mahajan, A., Wareham, N. J., Hofer, E., Joshi, P. K., Kristiansson, K., Traglia, M., Havulinna, A. S., Goel, A., Nalls, M. A., Sõber, S., Vuckovic, D., Luan, J., Del Greco M, F., Ayers, K. L., Marrugat, J., Ruggiero, D., Lopez, L. M., Niiranen, T., Enroth, S., Jackson, A. U., Nelson, C. P., Huffman, J. E., Zhang, W., Marten, J., Gandin, I., Harris, S. E., Zemunik, T., Lu, Y., Evangelou, E., Shah, N., de Borst, M. H., Mangino, M., Prins, B. P., Campbell, A., Li-Gao, R., Chauhan, G., Oldmeadow, C., Abecasis, G., Abedi, M., Barbieri, C. M., Barnes, M. R., Batini, C., Beilby, J., Blake, T., Boehnke, M., Bottinger, E. P., Braund, P. S., Brown, M., Brumat, M., Campbell, H., Chambers, J. C., Cocca, M., Collins, F., Connell, J., Cordell, H. J., Damman, J. J., Davies, G., de Geus, E. J., de Mutsert, R., Deelen, J., Demirkale, Y., Doney, A. S. F., Dörr, M., Farrall, M., Ferreira, T., Frånberg, M., Gao, H., Giedraitis, V., Gieger, C., Giulianini, F., Gow, A. J., Hamsten, A., Harris, T. B., Hofman, A., Holliday, E. G., Hui, J., Jarvelin, M. R., Johansson, �. �., Johnson, A. D., Jousilahti, P., Jula, A., Kähönen, M., Kathiresan, S., Khaw, K. T., Kolcic, I., Koskinen, S., Langenberg, C., Larson, M., Launer, L. J., Lehne, B., Liewald, D. C. M., Lin, L., Lind, L., Mach, F., Mamasoula, C., Menni, C., Mifsud, B., Milaneschi, Y., Morgan, A., Morris, A. D., Morrison, A. C., Munson, P. J., Nandakumar, P., Nguyen, Q. T., Nutile, T., Oldehinkel, A. J., Oostra, B. A., Org, E., Padmanabhan, S., Palotie, A., Paré, G., Pattie, A., Penninx, B. W. J. H., Poulter, N., Pramstaller, P. P., Raitakari, O. T., Ren, M., Rice, K., Ridker, P. M., Riese, H., Ripatti, S., Robino, A., Rotter, J. I., Rudan, I., Saba, Y., Saint Pierre, A., Sala, C. F., Sarin, A. P., Schmidt, R., Scott, R., Seelen, M. A., Shields, D. C., Siscovick, D., Sorice, R., Stanton, A., Stott, D. J., Sundström, J., Swertz, M., Taylor, K. D., Thom, S., Tzoulaki, I., Tzourio, C., Uitterlinden, A. G., Völker, U., Vollenweider, P., Wild, S., Willemsen, G., Wright, A. F., Yao, J., Thériault, S., Conen, D., Attia, J., Sever, P., Debette, S., Mook-Kanamori, D. O., Zeggini, E., Spector, T. D., van der Harst, P., Palmer, C. N. A., Vergnaud, A. C., Loos, R. J. F., Polasek, O., Starr, J. M., Girotto, G., Hayward, C., Kooner, J. S., Lindgren, C. M., Vitart, V., Samani, N. J., Tuomilehto, J., Gyllensten, U., Knekt, P., Deary, I. J., Ciullo, M., Elosua, R., Keavney, B. D., Hicks, A. A., Scott, R. A., Gasparini, P., Laan, M., Liu, Y., Watkins, H., Hartman, C. A., Salomaa, V., Toniolo, D., Perola, M., Wilson, J. F., Schmidt, H., Zhao, J. H., Lehtimäki, T., van Duijn, C. M., Gudnason, V., Psaty, B. M., Peters, A., Rettig, R., James, A., Jukema, J. W., Strachan, D. P., Palmas, W., Metspalu, A., Ingelsson, E., Boomsma, D. I., Franco, O. H., Bochud, M., Newton-Cheh, C., Munroe, P. B., Elliott, P., Chasman, D. I., Chakravarti, A., Knight, J., Morris, A. P., Levy, D., Tobin, M. D., Snieder, H., Caulfield, M. J., & Ehret, G. B. (2017). Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney. Hypertension (Dallas, Tex. : 1979), . https://doi.org/10.1161/HYPERTENSIONAHA.117.09438
Wain, Louise V, et al. "Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney." Hypertension (Dallas, Tex. : 1979) vol. (2017). doi: https://doi.org/10.1161/HYPERTENSIONAHA.117.09438
Wain LV, Vaez A, Jansen R, Joehanes R, van der Most PJ, Erzurumluoglu AM, O'Reilly PF, Cabrera CP, Warren HR, Rose LM, Verwoert GC, Hottenga JJ, Strawbridge RJ, Esko T, Arking DE, Hwang SJ, Guo X, Kutalik Z, Trompet S, Shrine N, Teumer A, Ried JS, Bis JC, Smith AV, Amin N, Nolte IM, Lyytikäinen LP, Mahajan A, Wareham NJ, Hofer E, Joshi PK, Kristiansson K, Traglia M, Havulinna AS, Goel A, Nalls MA, Sõber S, Vuckovic D, Luan J, Del Greco M F, Ayers KL, Marrugat J, Ruggiero D, Lopez LM, Niiranen T, Enroth S, Jackson AU, Nelson CP, Huffman JE, Zhang W, Marten J, Gandin I, Harris SE, Zemunik T, Lu Y, Evangelou E, Shah N, de Borst MH, Mangino M, Prins BP, Campbell A, Li-Gao R, Chauhan G, Oldmeadow C, Abecasis G, Abedi M, Barbieri CM, Barnes MR, Batini C, Beilby J, Blake T, Boehnke M, Bottinger EP, Braund PS, Brown M, Brumat M, Campbell H, Chambers JC, Cocca M, Collins F, Connell J, Cordell HJ, Damman JJ, Davies G, de Geus EJ, de Mutsert R, Deelen J, Demirkale Y, Doney ASF, Dörr M, Farrall M, Ferreira T, Frånberg M, Gao H, Giedraitis V, Gieger C, Giulianini F, Gow AJ, Hamsten A, Harris TB, Hofman A, Holliday EG, Hui J, Jarvelin MR, Johansson Å, Johnson AD, Jousilahti P, Jula A, Kähönen M, Kathiresan S, Khaw KT, Kolcic I, Koskinen S, Langenberg C, Larson M, Launer LJ, Lehne B, Liewald DCM, Lin L, Lind L, Mach F, Mamasoula C, Menni C, Mifsud B, Milaneschi Y, Morgan A, Morris AD, Morrison AC, Munson PJ, Nandakumar P, Nguyen QT, Nutile T, Oldehinkel AJ, Oostra BA, Org E, Padmanabhan S, Palotie A, Paré G, Pattie A, Penninx BWJH, Poulter N, Pramstaller PP, Raitakari OT, Ren M, Rice K, Ridker PM, Riese H, Ripatti S, Robino A, Rotter JI, Rudan I, Saba Y, Saint Pierre A, Sala CF, Sarin AP, Schmidt R, Scott R, Seelen MA, Shields DC, Siscovick D, Sorice R, Stanton A, Stott DJ, Sundström J, Swertz M, Taylor KD, Thom S, Tzoulaki I, Tzourio C, Uitterlinden AG, Völker U, Vollenweider P, Wild S, Willemsen G, Wright AF, Yao J, Thériault S, Conen D, Attia J, Sever P, Debette S, Mook-Kanamori DO, Zeggini E, Spector TD, van der Harst P, Palmer CNA, Vergnaud AC, Loos RJF, Polasek O, Starr JM, Girotto G, Hayward C, Kooner JS, Lindgren CM, Vitart V, Samani NJ, Tuomilehto J, Gyllensten U, Knekt P, Deary IJ, Ciullo M, Elosua R, Keavney BD, Hicks AA, Scott RA, Gasparini P, Laan M, Liu Y, Watkins H, Hartman CA, Salomaa V, Toniolo D, Perola M, Wilson JF, Schmidt H, Zhao JH, Lehtimäki T, van Duijn CM, Gudnason V, Psaty BM, Peters A, Rettig R, James A, Jukema JW, Strachan DP, Palmas W, Metspalu A, Ingelsson E, Boomsma DI, Franco OH, Bochud M, Newton-Cheh C, Munroe PB, Elliott P, Chasman DI, Chakravarti A, Knight J, Morris AP, Levy D, Tobin MD, Snieder H, Caulfield MJ, Ehret GB. Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney. Hypertension. 2017 Jul 24; doi: 10.1161/HYPERTENSIONAHA.117.09438. Epub 2017 Jul 24. PMID: 28739976; PMCID: PMC5783787.
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Thrown for a (stem) loop: How RNA structure impacts circular RNA regulation and function.

Methods (San Diego, Calif.)

Busa VF, Leung AKL.
PMID: 33662561
Methods. 2021 Dec;196:56-67. doi: 10.1016/j.ymeth.2021.02.019. Epub 2021 Mar 02.

Exonic circular RNAs (circRNAs) are RNA molecules that are covalently closed by back-splicing via canonical splicing machinery. Despite overlapping sequences, exon circularization generates RNA secondary structures through intramolecular base-pairing that are different from the linear transcript. Here we review...

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Busa VF, Leung AKL. Thrown for a (stem) loop: How RNA structure impacts circular RNA regulation and function. Methods. 2021;196:56-67doi: 10.1016/j.ymeth.2021.02.019.
Busa, V. F., & Leung, A. K. L. (2021). Thrown for a (stem) loop: How RNA structure impacts circular RNA regulation and function. Methods (San Diego, Calif.), 19656-67. https://doi.org/10.1016/j.ymeth.2021.02.019
Busa, Veronica F, and Leung, Anthony K L. "Thrown for a (stem) loop: How RNA structure impacts circular RNA regulation and function." Methods (San Diego, Calif.) vol. 196 (2021): 56-67. doi: https://doi.org/10.1016/j.ymeth.2021.02.019
Busa VF, Leung AKL. Thrown for a (stem) loop: How RNA structure impacts circular RNA regulation and function. Methods. 2021 Dec;196:56-67. doi: 10.1016/j.ymeth.2021.02.019. Epub 2021 Mar 02. PMID: 33662561.
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Correction: Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines.

British journal of cancer

Kagohara LT, Zamuner F, Davis-Marcisak EF, Sharma G, Considine M, Allen J, Yegnasubramanian S, Gaykalova DA, Fertig EJ.
PMID: 32694696
Br J Cancer. 2020 Nov;123(10):1582-1583. doi: 10.1038/s41416-020-0998-0.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Kagohara LT, Zamuner F, Davis-Marcisak EF, et al. Correction: Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines. Br J Cancer. 2020;123(10):1582-1583doi: 10.1038/s41416-020-0998-0.
Kagohara, L. T., Zamuner, F., Davis-Marcisak, E. F., Sharma, G., Considine, M., Allen, J., Yegnasubramanian, S., Gaykalova, D. A., & Fertig, E. J. (2020). Correction: Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines. British journal of cancer, 123(10), 1582-1583. https://doi.org/10.1038/s41416-020-0998-0
Kagohara, Luciane T, et al. "Correction: Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines." British journal of cancer vol. 123,10 (2020): 1582-1583. doi: https://doi.org/10.1038/s41416-020-0998-0
Kagohara LT, Zamuner F, Davis-Marcisak EF, Sharma G, Considine M, Allen J, Yegnasubramanian S, Gaykalova DA, Fertig EJ. Correction: Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines. Br J Cancer. 2020 Nov;123(10):1582-1583. doi: 10.1038/s41416-020-0998-0. PMID: 32694696; PMCID: PMC7652830.
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Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer.

Nature cancer

Anagnostou V, Niknafs N, Marrone K, Bruhm DC, White JR, Naidoo J, Hummelink K, Monkhorst K, Lalezari F, Lanis M, Rosner S, Reuss JE, Smith KN, Adleff V, Rodgers K, Belcaid Z, Rhymee L, Levy B, Feliciano J, Hann CL, Ettinger DS, Georgiades C, Verde F, Illei P, Li QK, Baras AS, Gabrielson E, Brock MV, Karchin R, Pardoll DM, Baylin SB, Brahmer JR, Scharpf RB, Forde PM, Velculescu VE.
PMID: 32984843
Nat Cancer. 2020 Jan;1(1):99-111. doi: 10.1038/s43018-019-0008-8. Epub 2020 Jan 13.

Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low...

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Anagnostou V, Niknafs N, Marrone K, et al. Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer. Nat Cancer. 2020;1(1):99-111doi: 10.1038/s43018-019-0008-8.
Anagnostou, V., Niknafs, N., Marrone, K., Bruhm, D. C., White, J. R., Naidoo, J., Hummelink, K., Monkhorst, K., Lalezari, F., Lanis, M., Rosner, S., Reuss, J. E., Smith, K. N., Adleff, V., Rodgers, K., Belcaid, Z., Rhymee, L., Levy, B., Feliciano, J., Hann, C. L., Ettinger, D. S., Georgiades, C., Verde, F., Illei, P., Li, Q. K., Baras, A. S., Gabrielson, E., Brock, M. V., Karchin, R., Pardoll, D. M., Baylin, S. B., Brahmer, J. R., Scharpf, R. B., Forde, P. M., & Velculescu, V. E. (2020). Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer. Nature cancer, 1(1), 99-111. https://doi.org/10.1038/s43018-019-0008-8
Anagnostou, Valsamo, et al. "Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer." Nature cancer vol. 1,1 (2020): 99-111. doi: https://doi.org/10.1038/s43018-019-0008-8
Anagnostou V, Niknafs N, Marrone K, Bruhm DC, White JR, Naidoo J, Hummelink K, Monkhorst K, Lalezari F, Lanis M, Rosner S, Reuss JE, Smith KN, Adleff V, Rodgers K, Belcaid Z, Rhymee L, Levy B, Feliciano J, Hann CL, Ettinger DS, Georgiades C, Verde F, Illei P, Li QK, Baras AS, Gabrielson E, Brock MV, Karchin R, Pardoll DM, Baylin SB, Brahmer JR, Scharpf RB, Forde PM, Velculescu VE. Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer. Nat Cancer. 2020 Jan;1(1):99-111. doi: 10.1038/s43018-019-0008-8. Epub 2020 Jan 13. PMID: 32984843; PMCID: PMC7514475.
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A map of mobile DNA insertions in the NCI-60 human cancer cell panel.

Mobile DNA

Zampella JG, Rodić N, Yang WR, Huang CR, Welch J, Gnanakkan VP, Cornish TC, Boeke JD, Burns KH.
PMID: 27807467
Mob DNA. 2016 Oct 31;7:20. doi: 10.1186/s13100-016-0078-4. eCollection 2016.

BACKGROUND: The National Cancer Institute-60 (NCI-60) cell lines are among the most widely used models of human cancer. They provide a platform to integrate DNA sequence information, epigenetic data, RNA and protein expression, and pharmacologic susceptibilities in studies of...

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Zampella JG, Rodić N, Yang WR, et al. A map of mobile DNA insertions in the NCI-60 human cancer cell panel. Mob DNA. 2016;7:20doi: 10.1186/s13100-016-0078-4.
Zampella, J. G., Rodić, N., Yang, W. R., Huang, C. R., Welch, J., Gnanakkan, V. P., Cornish, T. C., Boeke, J. D., & Burns, K. H. (2016). A map of mobile DNA insertions in the NCI-60 human cancer cell panel. Mobile DNA, 720. https://doi.org/10.1186/s13100-016-0078-4
Zampella, John G, et al. "A map of mobile DNA insertions in the NCI-60 human cancer cell panel." Mobile DNA vol. 7 (2016): 20. doi: https://doi.org/10.1186/s13100-016-0078-4
Zampella JG, Rodić N, Yang WR, Huang CR, Welch J, Gnanakkan VP, Cornish TC, Boeke JD, Burns KH. A map of mobile DNA insertions in the NCI-60 human cancer cell panel. Mob DNA. 2016 Oct 31;7:20. doi: 10.1186/s13100-016-0078-4. eCollection 2016. PMID: 27807467; PMCID: PMC5087121.
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Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism.

Frontiers in genetics

Pirooznia M, Niranjan T, Chen YC, Tunc I, Goes FS, Avramopoulos D, Potash JB, Huganir RL, Zandi PP, Wang T.
PMID: 31827489
Front Genet. 2019 Nov 27;10:1186. doi: 10.3389/fgene.2019.01186. eCollection 2019.

Autism spectrum disorders (ASDs) are characterized by deficits in three core behavioral domains: reciprocal social interactions, communication, and restricted interests and/or repetitive behaviors. Several hundreds of risk genes for autism have been identified, however, it remains a challenge to...

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Pirooznia M, Niranjan T, Chen YC, et al. Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism. Front Genet. 2019;10:1186doi: 10.3389/fgene.2019.01186.
Pirooznia, M., Niranjan, T., Chen, Y. C., Tunc, I., Goes, F. S., Avramopoulos, D., Potash, J. B., Huganir, R. L., Zandi, P. P., & Wang, T. (2019). Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism. Frontiers in genetics, 101186. https://doi.org/10.3389/fgene.2019.01186
Pirooznia, Mehdi, et al. "Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism." Frontiers in genetics vol. 10 (2019): 1186. doi: https://doi.org/10.3389/fgene.2019.01186
Pirooznia M, Niranjan T, Chen YC, Tunc I, Goes FS, Avramopoulos D, Potash JB, Huganir RL, Zandi PP, Wang T. Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism. Front Genet. 2019 Nov 27;10:1186. doi: 10.3389/fgene.2019.01186. eCollection 2019. PMID: 31827489; PMCID: PMC6892440.
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Identification and functional studies of regulatory variants responsible for the association of .

Molecular neuropsychiatry

Zeledón M, Eckart N, Taub M, Vernon H, Szymanksi M, Wang R, Chen PL, Nestadt G, McGrath JA, Sawa A, Pulver AE, Avramopoulos D, Valle D.
PMID: 26528484
Mol Neuropsychiatry. 2015 May;1(1):36-46. doi: 10.1159/000371518. Epub 2015 Feb 27.

We previously reported genetic linkage for Schizophrenia (SZ) (NPL of 4.7) at 10q22 in the Ashkenazi Jewish (AJ) population. In follow up fine mapping we found strong evidence of association between three intronic single nucleotide variants (SNVs) in the...

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Zeledón M, Eckart N, Taub M, et al. Identification and functional studies of regulatory variants responsible for the association of . Mol Neuropsychiatry. 2015;1(1):36-46doi: 10.1159/000371518.
Zeledón, M., Eckart, N., Taub, M., Vernon, H., Szymanksi, M., Wang, R., Chen, P. L., Nestadt, G., McGrath, J. A., Sawa, A., Pulver, A. E., Avramopoulos, D., & Valle, D. (2015). Identification and functional studies of regulatory variants responsible for the association of . Molecular neuropsychiatry, 1(1), 36-46. https://doi.org/10.1159/000371518
Zeledón, Mariela, et al. "Identification and functional studies of regulatory variants responsible for the association of ." Molecular neuropsychiatry vol. 1,1 (2015): 36-46. doi: https://doi.org/10.1159/000371518
Zeledón M, Eckart N, Taub M, Vernon H, Szymanksi M, Wang R, Chen PL, Nestadt G, McGrath JA, Sawa A, Pulver AE, Avramopoulos D, Valle D. Identification and functional studies of regulatory variants responsible for the association of . Mol Neuropsychiatry. 2015 May;1(1):36-46. doi: 10.1159/000371518. Epub 2015 Feb 27. PMID: 26528484; PMCID: PMC4627703.
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Somatic mosaicism in the human genome.

Genes

Freed D, Stevens EL, Pevsner J.
PMID: 25513881
Genes (Basel). 2014 Dec 11;5(4):1064-94. doi: 10.3390/genes5041064.

Somatic mosaicism refers to the occurrence of two genetically distinct populations of cells within an individual, derived from a postzygotic mutation. In contrast to inherited mutations, somatic mosaic mutations may affect only a portion of the body and are...

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Freed D, Stevens EL, Pevsner J. Somatic mosaicism in the human genome. Genes (Basel). 2014;5(4):1064-94doi: 10.3390/genes5041064.
Freed, D., Stevens, E. L., & Pevsner, J. (2014). Somatic mosaicism in the human genome. Genes, 5(4), 1064-94. https://doi.org/10.3390/genes5041064
Freed, Donald, et al. "Somatic mosaicism in the human genome." Genes vol. 5,4 (2014): 1064-94. doi: https://doi.org/10.3390/genes5041064
Freed D, Stevens EL, Pevsner J. Somatic mosaicism in the human genome. Genes (Basel). 2014 Dec 11;5(4):1064-94. doi: 10.3390/genes5041064. PMID: 25513881; PMCID: PMC4276927.
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Neuregulin 3 Knockout Mice Exhibit Behaviors Consistent with Psychotic Disorders.

Molecular neuropsychiatry

Hayes LN, Shevelkin A, Zeledon M, Steel G, Chen PL, Obie C, Pulver A, Avramopoulos D, Valle D, Sawa A, Pletnikov MV.
PMID: 27606322
Mol Neuropsychiatry. 2016 Jul;2(2):79-87. doi: 10.1159/000445836. Epub 2016 May 20.

Neuregulin 3 (NRG3) is a paralog of NRG1. Genetic studies in schizophrenia demonstrate that risk variants in NRG3 are associated with cognitive and psychotic symptom severity, and several intronic single nucleotide polymorphisms in NRG3 are associated with delusions in...

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Hayes LN, Shevelkin A, Zeledon M, et al. Neuregulin 3 Knockout Mice Exhibit Behaviors Consistent with Psychotic Disorders. Mol Neuropsychiatry. 2016;2(2):79-87doi: 10.1159/000445836.
Hayes, L. N., Shevelkin, A., Zeledon, M., Steel, G., Chen, P. L., Obie, C., Pulver, A., Avramopoulos, D., Valle, D., Sawa, A., & Pletnikov, M. V. (2016). Neuregulin 3 Knockout Mice Exhibit Behaviors Consistent with Psychotic Disorders. Molecular neuropsychiatry, 2(2), 79-87. https://doi.org/10.1159/000445836
Hayes, Lindsay N, et al. "Neuregulin 3 Knockout Mice Exhibit Behaviors Consistent with Psychotic Disorders." Molecular neuropsychiatry vol. 2,2 (2016): 79-87. doi: https://doi.org/10.1159/000445836
Hayes LN, Shevelkin A, Zeledon M, Steel G, Chen PL, Obie C, Pulver A, Avramopoulos D, Valle D, Sawa A, Pletnikov MV. Neuregulin 3 Knockout Mice Exhibit Behaviors Consistent with Psychotic Disorders. Mol Neuropsychiatry. 2016 Jul;2(2):79-87. doi: 10.1159/000445836. Epub 2016 May 20. PMID: 27606322; PMCID: PMC4996025.
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Deep resequencing of .

Human genome variation

Vecchio-Pagán B, Blackman SM, Lee M, Atalar M, Pellicore MJ, Pace RG, Franca AL, Raraigh KS, Sharma N, Knowles MR, Cutting GR.
PMID: 27917292
Hum Genome Var. 2016 Nov 24;3:16038. doi: 10.1038/hgv.2016.38. eCollection 2016.

Extensive phenotypic variability is commonly observed in individuals with Mendelian disorders, even among those with identical genotypes in the disease-causing gene. To determine whether variants within and surrounding

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Vecchio-Pagán B, Blackman SM, Lee M, et al. Deep resequencing of . Hum Genome Var. 2016;3:16038doi: 10.1038/hgv.2016.38.
Vecchio-Pagán, B., Blackman, S. M., Lee, M., Atalar, M., Pellicore, M. J., Pace, R. G., Franca, A. L., Raraigh, K. S., Sharma, N., Knowles, M. R., & Cutting, G. R. (2016). Deep resequencing of . Human genome variation, 316038. https://doi.org/10.1038/hgv.2016.38
Vecchio-Pagán, Briana, et al. "Deep resequencing of ." Human genome variation vol. 3 (2016): 16038. doi: https://doi.org/10.1038/hgv.2016.38
Vecchio-Pagán B, Blackman SM, Lee M, Atalar M, Pellicore MJ, Pace RG, Franca AL, Raraigh KS, Sharma N, Knowles MR, Cutting GR. Deep resequencing of . Hum Genome Var. 2016 Nov 24;3:16038. doi: 10.1038/hgv.2016.38. eCollection 2016. PMID: 27917292; PMCID: PMC5121184.
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