Searching journal content for articles similar to Natsoulis et al. 15 (5): 724.

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  1. LETTER: Coexpression Analysis of Human Genes Across Many Microarray Data Sets
    • Homin K. Lee,
    • Amy K. Hsu,
    • Jon Sajdak,
    • Jie Qin,
    • and Paul Pavlidis
    Genome Res. June 2004 14: 1085-1094; doi:10.1101/gr.1910904
    ...approach yields a high-level overview, it is difficult to study individual genes in the network in this manner, and it was difficult to analyze larger networks. Therefore to analyze the network of 3+ confirmed genes, we used a second approach based on MCODE, an algorithm designed to identify groups...
  2. Method: Robust and efficient annotation of cell states through gene signature scoring
    • Laure Ciernik,
    • Agnieszka Kraft,
    • Florian Barkmann,
    • Josephine Yates,
    • and Valentina Boeva
    Genome Res. March 2026 36: 630-644; Published in Advance February 18, 2026, doi:10.1101/gr.280926.125
    ..., UCell, and JASMINE—across nine healthy and cancer scRNA-seq data sets demonstrates their insufficiency in fulfilling this requirement. To address this limitation, we present Adjusted Neighborhood Scoring (ANS), a deterministic algorithm with enhanced control gene selection that significantly improves...
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  3. Research: Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution
    • Justyna A. Resztak,
    • Julong Wei,
    • Samuele Zilioli,
    • Edward Sendler,
    • Adnan Alazizi,
    • Henriette E. Mair-Meijers,
    • Peijun Wu,
    • Xiaoquan Wen,
    • Richard B. Slatcher,
    • Xiang Zhou,
    • Francesca Luca,
    • and Roger Pique-Regi
    Genome Res. June 2023 33: 839-856; Published in Advance July 13, 2023, doi:10.1101/gr.276765.122
    ...(Supplemental Fig. S19).Characterizing dynamic responsesSingle-cell transcriptomics can also be used to study heterogeneous cell states during important biological processes, such as cell type differentiation during development (Mohammed et al. 2017; Cuomo et al. 2020). Most algorithms developed to study cell...
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  4. Method: Identification of phenotype-specific networks from paired gene expression–cell shape imaging data
    • Charlie George Barker,
    • Eirini Petsalaki,
    • Girolamo Giudice,
    • Julia Sero,
    • Emmanuel Nsa Ekpenyong,
    • Chris Bakal,
    • and Evangelia Petsalaki
    Genome Res. April 2022 32: 750-765; Published in Advance February 23, 2022, doi:10.1101/gr.276059.121
    ....11% of the genes identified by our analysis. The new proteins that were included by the PCSF algorithm to maximize prize collection showed gene set enrichment of common terms (Pathways from PANTHER) (Mi et al. 2013) relative to the original prizes (including WNT, EGF, angiogenesis, RAS, cadherin, and TGFB pathways...
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  5. Method: HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology
    • Raunak Shrestha,
    • Ermin Hodzic,
    • Thomas Sauerwald,
    • Phuong Dao,
    • Kendric Wang,
    • Jake Yeung,
    • Shawn Anderson,
    • Fabio Vandin,
    • Gholamreza Haffari,
    • Colin C. Collins,
    • and S. Cenk Sahinalp
    Genome Res. September 2017 27: 1573-1588; Published in Advance July 18, 2017, doi:10.1101/gr.221218.117
    ...either aMarkov chainMonteCarlo algorithm or integer linear programming (ILP). XSEQ (Ding et al. 2015) uses probabilistic model to compute influence of mutated genes over expression profile changes in other genes by considering direct gene interactions. Finally, MEMo (Ciriello et al. 2012) identifies sets...
  6. Research: Hydroxycarbamide effects on DNA methylation and gene expression in myeloproliferative neoplasms
    • Stephania Contreras Castillo,
    • Bertille Montibus,
    • Azucena Rocha,
    • Will Duke,
    • Ferdinand von Meyenn,
    • Donal McLornan,
    • Claire Harrison,
    • Ann Mullally,
    • Reiner Schulz,
    • and Rebecca J. Oakey
    Genome Res. August 2021 31: 1381-1394; Published in Advance July 9, 2021, doi:10.1101/gr.270066.120
    ...was measured -wide with the Infinium Human MethylationEPIC BeadArray (Illumina). Raw files were processed in R (version 3.5.1) (R Core Team 2018). Quality control was performed using Minfi (version 1.28.4) (Aryee et al. 2014), and RnBeads's Greedy cut algorithm (version 2.0.1) (Assenov et al. 2014). Background...
  7. Method: Linking signaling pathways to transcriptional programs in breast cancer
    • Hatice U. Osmanbeyoglu,
    • Raphael Pelossof,
    • Jacqueline F. Bromberg,
    • and Christina S. Leslie
    Genome Res. November 2014 24: 1869-1880; Published in Advance September 2, 2014, doi:10.1101/gr.173039.114
    ...readout of the activity of signaling pathways; oncogenic signaling pathways converge on a set of transcription factors (TFs), whose dysregulated activity in turn alters the mRNA expression levels of TF target genes. Formally, we use an algorithm we recently developed, called affinity regression (R...
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  8. Research: Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer
    • Jung H. Kim,
    • Saravana M. Dhanasekaran,
    • John R. Prensner,
    • Xuhong Cao,
    • Daniel Robinson,
    • Shanker Kalyana-Sundaram,
    • Christina Huang,
    • Sunita Shankar,
    • Xiaojun Jing,
    • Matthew Iyer,
    • Ming Hu,
    • Lee Sam,
    • Catherine Grasso,
    • Christopher A. Maher,
    • Nallasivam Palanisamy,
    • Rohit Mehra,
    • Hal D. Kominsky,
    • Javed Siddiqui,
    • Jindan Yu,
    • Zhaohui S. Qin,
    • and Arul M. Chinnaiyan
    Genome Res. July 2011 21: 1028-1041; doi:10.1101/gr.119347.110
    ...(Supplemental Table 1) and showed maximum overlap (;70%) with methylation identified by hybridizing the MethylPlex product to a CpG island array (Supplemental Fig. 3A; Supplemental Table 2). We therefore selected these data for further analysis. A hidden Markov model (HMM)–based algorithm previously used for Ch...
  9. Method: Single-cell RNA-seq analysis identifies markers of resistance to targeted BRAF inhibitors in melanoma cell populations
    • Yu-Jui Ho,
    • Naishitha Anaparthy,
    • David Molik,
    • Grinu Mathew,
    • Toby Aicher,
    • Ami Patel,
    • James Hicks,
    • and Molly Gale Hammell
    Genome Res. September 2018 28: 1353-1363; Published in Advance July 30, 2018, doi:10.1101/gr.234062.117
    ...these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors (BRAFi). Single-cell RNA-seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE...
  10. Perspective: The path to routine use of genomic biomarkers in the cancer clinic
    • Paul C. Boutros
    Genome Res. October 2015 25: 1508-1513; doi:10.1101/gr.191114.115
    ...operational ways of identifying it (Lapuk et al. 2012; Govind et al. 2014). Similarly, there is not yet a standard library of mutational signatures or standard algorithms to call them uniformly across data sets. The same is true for localized hypermutationatthepoint-mutation level suchaskataegis...
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