Page Comparison

This page is an incomplete list of published papers which harnessed the O2 cluster, the now-retired Orchestra cluster, and/or acknowledge members of the HMS RC group. We always encourage researchers to mention HMS RC staff and O2 in their acknowledgements as appropriate, or as co-authors for substantial contributions. We appreciate it if you could contact us about such papers, so we can list them below. For computational labs doing work on O2 (or previously on Orchestra), we're happy to link your publications page!

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Portions of this research were conducted on the O2 High Performance Compute Cluster, supported by the Research Computing Group, at Harvard Medical School. See httphttps://rcit.hms.harvard.edu /our-services/research-computing for more information.

If you received support from the Research Computing Consultant Group (RCCG) that contributed to your work, but is not substantial enough to warrant co-authorship, please use text similar to the following. You can optionally mention specific consultants:

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• Romero, J et al. Statistical efficiency of patient data in randomized clinical trials of epilepsy treatments. DOI: 10.1111/epi.16609

• Goldenholz, D et al. Development and Validation of Forecasting Next Reported Seizure Using e-Diaries.  ANN NEUROL 2020;00:1–8

• Oliveira, A et al. Comparing the efficacy, exposure, and cost of clinical trial analysis methods. DOI: 10.1111/epi.16384

• Romero, J et al. Natural variability in seizure frequency: Implications for trials and placebo. Epilepsy Research 162 (2020) 106306

• Letswaart,R et al. GeneWalk identifies relevant gene functions for a biological context using network representation learning. Genome Biology volume 22, Article number: 55 (2021) 

• Schoech, A. P. et al. Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection. Nature Communications 10, 790 (2019).

• AlQuraishi, M. End-to-End Differentiable Learning of Protein Structure. Cell Systems 8, 292-301.e3 (2019).

• Loh, P.-R., Kichaev, G., Gazal, S., Schoech, A. P. & Price, A. L. Mixed-model association for biobank-scale datasets. Nature Genetics 50, 906 (2018).

• Loh PR, Danecek P, Palamara PF, Fuchsberger C, Reshef YA, Finucane HK, Schoenherr S, Forer L, McCarthy S, Abecasis GR, Durbin R, Price AL. (2016) "Reference-based phasing using the Haplotype Reference Consortium panel", Nature Genetics 48, 1443.
• Virginia Savova, Jon Patsenker, Sébastien Vigneau and Alexander A. Gimelbrant. (2015) "dbMAE: the database of autosomal monoallelic expression", Nucleic Acids Research, 10.1093/nar/gkv1106
• Li Li and Jack W. Szostak, (2014) "The Free Energy Landscape of Pseudorotation in 3′–5′ and 2′–5′ Linked Nucleic Acids", JACS, 2014 Feb 5; 136 (7), pp 2858–2865
• Gilad D. Evrony, Xuyu Cai, Eunjung Lee, L. Benjamin Hills, Princess C. Elhosary, Hillel S. Lehmann, J.J. Parker, Kutay D. Atabay, Edward C. Gilmore, Annapurna Poduri, Peter J. Park, Christopher A. Walsh. (2012) "Single-Neuron Sequencing Analysis of L1 Retrotransposition and Somatic Mutation in the Human Brain", Cell, 151 (3): 483–496
• Deluca TF, Cui J, Jung JY, St Gabriel KC, Wall DP. (2012) "Roundup 2.0: Enabling comparative genomics for over 1800 genomes", Bioinformatics, 28 (5): 715-716
• M. Ernebjerg and R. Kishony, (2011) "Distinct Growth Strategies of Soil Bacteria as Revealed by Large-Scale Colony Tracking", American Society for Microbiology, 10.1128/AEM.06585-11
• Barstow, B., C. M. Agapakis, et al. (2011). "A synthetic system links FeFe-hydrogenases to essential E. coli sulfur metabolism." J Biol Eng 5: 7.
• M. Ernebjerg and R. Kishony, (2011) "Dynamic phenotypic clustering in noisy ecosystems", PLoS Computational Biology, 7(3) e1002017
• J.M. Higgins and L. Mahadevan, (2010) "Physiological and pathological population dynamics of circulating human red blood cells.", PNAS, 2010 Nov 23;107(47):20587-92

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