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Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification.

Nature biotechnology

Bulik-Sullivan B, Busby J, Palmer CD, Davis MJ, Murphy T, Clark A, Busby M, Duke F, Yang A, Young L, Ojo NC, Caldwell K, Abhyankar J, Boucher T, Hart MG, Makarov V, Montpreville VT, Mercier O, Chan TA, Scagliotti G, Bironzo P, Novello S, Karachaliou N, Rosell R, Anderson I, Gabrail N, Hrom J, Limvarapuss C, Choquette K, Spira A, Rousseau R, Voong C, Rizvi NA, Fadel E, Frattini M, Jooss K, Skoberne M, Francis J, Yelensky R.
PMID: 30556813
Nat Biotechnol. 2018 Dec 17; doi: 10.1038/nbt.4313. Epub 2018 Dec 17.

Neoantigens, which are expressed on tumor cells, are one of the main targets of an effective antitumor T-cell response. Cancer immunotherapies to target neoantigens are of growing interest and are in early human trials, but methods to identify neoantigens...

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Bulik-Sullivan B, Busby J, Palmer CD, et al. Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification. Nat Biotechnol. 2018;doi: 10.1038/nbt.4313.
Bulik-Sullivan, B., Busby, J., Palmer, C. D., Davis, M. J., Murphy, T., Clark, A., Busby, M., Duke, F., Yang, A., Young, L., Ojo, N. C., Caldwell, K., Abhyankar, J., Boucher, T., Hart, M. G., Makarov, V., Montpreville, V. T., Mercier, O., Chan, T. A., Scagliotti, G., Bironzo, P., Novello, S., Karachaliou, N., Rosell, R., Anderson, I., Gabrail, N., Hrom, J., Limvarapuss, C., Choquette, K., Spira, A., Rousseau, R., Voong, C., Rizvi, N. A., Fadel, E., Frattini, M., Jooss, K., Skoberne, M., Francis, J., & Yelensky, R. (2018). Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification. Nature biotechnology, . https://doi.org/10.1038/nbt.4313
Bulik-Sullivan, Brendan, et al. "Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification." Nature biotechnology vol. (2018). doi: https://doi.org/10.1038/nbt.4313
Bulik-Sullivan B, Busby J, Palmer CD, Davis MJ, Murphy T, Clark A, Busby M, Duke F, Yang A, Young L, Ojo NC, Caldwell K, Abhyankar J, Boucher T, Hart MG, Makarov V, Montpreville VT, Mercier O, Chan TA, Scagliotti G, Bironzo P, Novello S, Karachaliou N, Rosell R, Anderson I, Gabrail N, Hrom J, Limvarapuss C, Choquette K, Spira A, Rousseau R, Voong C, Rizvi NA, Fadel E, Frattini M, Jooss K, Skoberne M, Francis J, Yelensky R. Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification. Nat Biotechnol. 2018 Dec 17; doi: 10.1038/nbt.4313. Epub 2018 Dec 17. PMID: 30556813.
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Author Correction: Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection.

Nature genetics

Gazal S, Finucane HK, Furlotte NA, Loh PR, Palamara PF, Liu X, Schoech A, Bulik-Sullivan B, Neale BM, Gusev A, Price AL.
PMID: 31273336
Nat Genet. 2019 Aug;51(8):1295. doi: 10.1038/s41588-019-0468-x.

In the version of the paper initially published, information on competing interests for author Benjamin M. Neale was missing. The 'Competing interests' statement should have included the sentence 'B.M.N. is on the Scientific Advisory Board of Deep Genomics'.

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Gazal S, Finucane HK, Furlotte NA, et al. Author Correction: Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nat Genet. 2019;51(8):1295doi: 10.1038/s41588-019-0468-x.
Gazal, S., Finucane, H. K., Furlotte, N. A., Loh, P. R., Palamara, P. F., Liu, X., Schoech, A., Bulik-Sullivan, B., Neale, B. M., Gusev, A., & Price, A. L. (2019). Author Correction: Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nature genetics, 51(8), 1295. https://doi.org/10.1038/s41588-019-0468-x
Gazal, Steven, et al. "Author Correction: Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection." Nature genetics vol. 51,8 (2019): 1295. doi: https://doi.org/10.1038/s41588-019-0468-x
Gazal S, Finucane HK, Furlotte NA, Loh PR, Palamara PF, Liu X, Schoech A, Bulik-Sullivan B, Neale BM, Gusev A, Price AL. Author Correction: Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nat Genet. 2019 Aug;51(8):1295. doi: 10.1038/s41588-019-0468-x. PMID: 31273336.
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Correction: The Gut-Brain Axis in Healthy Females: Lack of Significant Association between Microbial Composition and Diversity with Psychiatric Measures.

PloS one

Kleiman SC, Bulik-Sullivan EC, Glenny EM, Zerwas SC, Huh EY, Tsilimigras MCB, Fodor AA, Bulik CM, Carroll IM.
PMID: 31437250
PLoS One. 2019 Aug 22;14(8):e0221724. doi: 10.1371/journal.pone.0221724. eCollection 2019.

[This corrects the article DOI: 10.1371/journal.pone.0170208.].

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Kleiman SC, Bulik-Sullivan EC, Glenny EM, et al. Correction: The Gut-Brain Axis in Healthy Females: Lack of Significant Association between Microbial Composition and Diversity with Psychiatric Measures. PLoS One. 2019;14(8):e0221724doi: 10.1371/journal.pone.0221724.
Kleiman, S. C., Bulik-Sullivan, E. C., Glenny, E. M., Zerwas, S. C., Huh, E. Y., Tsilimigras, M. C. B., Fodor, A. A., Bulik, C. M., & Carroll, I. M. (2019). Correction: The Gut-Brain Axis in Healthy Females: Lack of Significant Association between Microbial Composition and Diversity with Psychiatric Measures. PloS one, 14(8), e0221724. https://doi.org/10.1371/journal.pone.0221724
Kleiman, Susan C, et al. "Correction: The Gut-Brain Axis in Healthy Females: Lack of Significant Association between Microbial Composition and Diversity with Psychiatric Measures." PloS one vol. 14,8 (2019): e0221724. doi: https://doi.org/10.1371/journal.pone.0221724
Kleiman SC, Bulik-Sullivan EC, Glenny EM, Zerwas SC, Huh EY, Tsilimigras MCB, Fodor AA, Bulik CM, Carroll IM. Correction: The Gut-Brain Axis in Healthy Females: Lack of Significant Association between Microbial Composition and Diversity with Psychiatric Measures. PLoS One. 2019 Aug 22;14(8):e0221724. doi: 10.1371/journal.pone.0221724. eCollection 2019. PMID: 31437250; PMCID: PMC6705793.
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Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci.

Molecular psychiatry

Smith DJ, Escott-Price V, Davies G, Bailey ME, Colodro-Conde L, Ward J, Vedernikov A, Marioni R, Cullen B, Lyall D, Hagenaars SP, Liewald DC, Luciano M, Gale CR, Ritchie SJ, Hayward C, Nicholl B, Bulik-Sullivan B, Adams M, Couvy-Duchesne B, Graham N, Mackay D, Evans J, Smith BH, Porteous DJ, Medland SE, Martin NG, Holmans P, McIntosh AM, Pell JP, Deary IJ, O'Donovan MC.
PMID: 27620839
Mol Psychiatry. 2016 Nov;21(11):1644. doi: 10.1038/mp.2016.177. Epub 2016 Sep 13.

No abstract available.

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Smith DJ, Escott-Price V, Davies G, et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol Psychiatry. 2016;21(11):1644doi: 10.1038/mp.2016.177.
Smith, D. J., Escott-Price, V., Davies, G., Bailey, M. E., Colodro-Conde, L., Ward, J., Vedernikov, A., Marioni, R., Cullen, B., Lyall, D., Hagenaars, S. P., Liewald, D. C., Luciano, M., Gale, C. R., Ritchie, S. J., Hayward, C., Nicholl, B., Bulik-Sullivan, B., Adams, M., Couvy-Duchesne, B., Graham, N., Mackay, D., Evans, J., Smith, B. H., Porteous, D. J., Medland, S. E., Martin, N. G., Holmans, P., McIntosh, A. M., Pell, J. P., Deary, I. J., & O'Donovan, M. C. (2016). Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Molecular psychiatry, 21(11), 1644. https://doi.org/10.1038/mp.2016.177
Smith, D J, et al. "Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci." Molecular psychiatry vol. 21,11 (2016): 1644. doi: https://doi.org/10.1038/mp.2016.177
Smith DJ, Escott-Price V, Davies G, Bailey ME, Colodro-Conde L, Ward J, Vedernikov A, Marioni R, Cullen B, Lyall D, Hagenaars SP, Liewald DC, Luciano M, Gale CR, Ritchie SJ, Hayward C, Nicholl B, Bulik-Sullivan B, Adams M, Couvy-Duchesne B, Graham N, Mackay D, Evans J, Smith BH, Porteous DJ, Medland SE, Martin NG, Holmans P, McIntosh AM, Pell JP, Deary IJ, O'Donovan MC. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol Psychiatry. 2016 Nov;21(11):1644. doi: 10.1038/mp.2016.177. Epub 2016 Sep 13. PMID: 27620839; PMCID: PMC5078853.
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Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice.

Gut microbes

Glenny EM, Fouladi F, Thomas SA, Bulik-Sullivan EC, Tang Q, Djukic Z, Trillo-Ordonez YS, A Fodor A, Tarantino LM, M Bulik C, M Carroll I.
PMID: 33769200
Gut Microbes. 2021 Jan-Dec;13(1):1-15. doi: 10.1080/19490976.2021.1897216.

Anorexia nervosa (AN) is a psychiatric disorder that presents with profound weight dysregulation, metabolic disturbances, and an abnormal composition of gut microbial communities. As the intestinal microbiota can influence host metabolism, the impact of enteric microbial communities from patients...

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Glenny EM, Fouladi F, Thomas SA, et al. Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice. Gut Microbes. 2021;13(1):1-15doi: 10.1080/19490976.2021.1897216.
Glenny, E. M., Fouladi, F., Thomas, S. A., Bulik-Sullivan, E. C., Tang, Q., Djukic, Z., Trillo-Ordonez, Y. S., A Fodor, A., Tarantino, L. M., M Bulik, C., & M Carroll, I. (2021). Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice. Gut microbes, 13(1), 1-15. https://doi.org/10.1080/19490976.2021.1897216
Glenny, Elaine M, et al. "Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice." Gut microbes vol. 13,1 (2021): 1-15. doi: https://doi.org/10.1080/19490976.2021.1897216
Glenny EM, Fouladi F, Thomas SA, Bulik-Sullivan EC, Tang Q, Djukic Z, Trillo-Ordonez YS, A Fodor A, Tarantino LM, M Bulik C, M Carroll I. Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice. Gut Microbes. 2021 Jan-Dec;13(1):1-15. doi: 10.1080/19490976.2021.1897216. PMID: 33769200; PMCID: PMC8007138.
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A microbial signature following bariatric surgery is robustly consistent across multiple cohorts.

Gut microbes

Fouladi F, Carroll IM, Sharpton TJ, Bulik-Sullivan E, Heinberg L, Steffen KJ, Fodor AA.
PMID: 34159880
Gut Microbes. 2021 Jan-Dec;13(1):1930872. doi: 10.1080/19490976.2021.1930872.

Bariatric surgery induces significant shifts in the gut microbiota which could potentially contribute to weight loss and metabolic benefits. The aim of this study was to characterize a microbial signature following Roux-en-Y Gastric bypass (RYGB) surgery using novel and...

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Fouladi F, Carroll IM, Sharpton TJ, et al. A microbial signature following bariatric surgery is robustly consistent across multiple cohorts. Gut Microbes. 2021;13(1):1930872doi: 10.1080/19490976.2021.1930872.
Fouladi, F., Carroll, I. M., Sharpton, T. J., Bulik-Sullivan, E., Heinberg, L., Steffen, K. J., & Fodor, A. A. (2021). A microbial signature following bariatric surgery is robustly consistent across multiple cohorts. Gut microbes, 13(1), 1930872. https://doi.org/10.1080/19490976.2021.1930872
Fouladi, Farnaz, et al. "A microbial signature following bariatric surgery is robustly consistent across multiple cohorts." Gut microbes vol. 13,1 (2021): 1930872. doi: https://doi.org/10.1080/19490976.2021.1930872
Fouladi F, Carroll IM, Sharpton TJ, Bulik-Sullivan E, Heinberg L, Steffen KJ, Fodor AA. A microbial signature following bariatric surgery is robustly consistent across multiple cohorts. Gut Microbes. 2021 Jan-Dec;13(1):1930872. doi: 10.1080/19490976.2021.1930872. PMID: 34159880; PMCID: PMC8224199.
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Showing 1 to 6 of 6 entries