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Breast Cancer

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PLoS Comput Biol
    June 2021
  1. ERDEM C, Lee AV, Taylor DL, Lezon TR, et al
    Inhibition of RPS6K reveals context-dependent Akt activity in luminal breast cancer cells.
    PLoS Comput Biol. 2021;17:e1009125.
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  2. TRENTHAM-DIETZ A, Alagoz O, Chapman C, Huang X, et al
    Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.
    PLoS Comput Biol. 2021;17:e1009020.
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    March 2021
  3. CLIMENTE-GONZALEZ H, Lonjou C, Lesueur F, Stoppa-Lyonnet D, et al
    Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer.
    PLoS Comput Biol. 2021;17:e1008819.
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    February 2021
  4. BEN-ELAZAR S, Aure MR, Jonsdottir K, Leivonen SK, et al
    miRNA normalization enables joint analysis of several datasets to increase sensitivity and to reveal novel miRNAs differentially expressed in breast cancer.
    PLoS Comput Biol. 2021;17:e1008608.
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  5. SUSAK H, Serra-Saurina L, Demidov G, Rabionet R, et al
    Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation.
    PLoS Comput Biol. 2021;17:e1007784.
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    January 2021
  6. GORDIN M, Philip H, Zilberberg A, Gidoni M, et al
    Breast cancer is marked by specific, Public T-cell receptor CDR3 regions shared by mice and humans.
    PLoS Comput Biol. 2021;17:e1008486.
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    November 2020
  7. SETHI R, Becker J, Graaf J, Lower M, et al
    Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions.
    PLoS Comput Biol. 2020;16:e1008397.
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    September 2020
  8. VAN DER KLOET FM, Buurmans J, Jonker MJ, Smilde AK, et al
    Increased comparability between RNA-Seq and microarray data by utilization of gene sets.
    PLoS Comput Biol. 2020;16:e1008295.
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    August 2020
  9. LI X, Liu L, Goodall GJ, Schreiber A, et al
    A novel single-cell based method for breast cancer prognosis.
    PLoS Comput Biol. 2020;16:e1008133.
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    July 2020
  10. LE TTT, Adler FR
    Is mammography screening beneficial: An individual-based stochastic model for breast cancer incidence and mortality.
    PLoS Comput Biol. 2020;16:e1008036.
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    May 2020
  11. WANG L, You ZH, Li YM, Zheng K, et al
    GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm.
    PLoS Comput Biol. 2020;16:e1007568.
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    April 2020
  12. ZHANG J, Xu T, Liu L, Zhang W, et al
    LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer.
    PLoS Comput Biol. 2020;16:e1007851.
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  13. YANG KD, Damodaran K, Venkatachalapathy S, Soylemezoglu AC, et al
    Predicting cell lineages using autoencoders and optimal transport.
    PLoS Comput Biol. 2020;16:e1007828.
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  14. VSEVOLOZHSKAYA OA, Shi M, Hu F, Zaykin DV, et al
    DOT: Gene-set analysis by combining decorrelated association statistics.
    PLoS Comput Biol. 2020;16:e1007819.
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    February 2020
  15. SCHAADT NS, Schonmeyer R, Forestier G, Brieu N, et al
    Graph-based description of tertiary lymphoid organs at single-cell level.
    PLoS Comput Biol. 2020;16:e1007385.
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    January 2020
  16. PADMANABAN V, Tsehay Y, Cheung KJ, Ewald AJ, et al
    Between-tumor and within-tumor heterogeneity in invasive potential.
    PLoS Comput Biol. 2020;16:e1007464.
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    December 2019
  17. KONIG SM, Rissler V, Terkelsen T, Lambrughi M, et al
    Alterations of the interactome of Bcl-2 proteins in breast cancer at the transcriptional, mutational and structural level.
    PLoS Comput Biol. 2019;15:e1007485.
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  18. WANG Y, Chen S, Chen L, Wang Y, et al
    Associating lncRNAs with small molecules via bilevel optimization reveals cancer-related lncRNAs.
    PLoS Comput Biol. 2019;15:e1007540.
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  19. PHAM VVH, Liu L, Bracken CP, Goodall GJ, et al
    CBNA: A control theory based method for identifying coding and non-coding cancer drivers.
    PLoS Comput Biol. 2019;15:e1007538.
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    October 2019
  20. CHAPMAN MP, Risom T, Aswani AJ, Langer EM, et al
    Correction: Modeling differentiation-state transitions linked to therapeutic escape in triple-negative breast cancer.
    PLoS Comput Biol. 2019;15:e1007441.
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    April 2019
  21. VARENNES J, Moon HR, Saha S, Mugler A, et al
    Physical constraints on accuracy and persistence during breast cancer cell chemotaxis.
    PLoS Comput Biol. 2019;15:e1006961.
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    March 2019
  22. CHAPMAN MP, Risom T, Aswani AJ, Langer EM, et al
    Modeling differentiation-state transitions linked to therapeutic escape in triple-negative breast cancer.
    PLoS Comput Biol. 2019;15:e1006840.
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  23. DE ALMEIDA BP, Vieira AF, Paredes J, Bettencourt-Dias M, et al
    Pan-cancer association of a centrosome amplification gene expression signature with genomic alterations and clinical outcome.
    PLoS Comput Biol. 2019;15:e1006832.
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    February 2019
  24. RUFFALO M, Thomas R, Chen J, Lee AV, et al
    Network-guided prediction of aromatase inhibitor response in breast cancer.
    PLoS Comput Biol. 2019;15:e1006730.
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  25. ALLAHYAR A, Ubels J, de Ridder J
    A data-driven interactome of synergistic genes improves network-based cancer outcome prediction.
    PLoS Comput Biol. 2019;15:e1006657.
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  26. DAMIANI C, Maspero D, Di Filippo M, Colombo R, et al
    Integration of single-cell RNA-seq data into population models to characterize cancer metabolism.
    PLoS Comput Biol. 2019;15:e1006733.
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    October 2018
  27. BISMEIJER T, Canisius S, Wessels LFA
    Molecular characterization of breast and lung tumors by integration of multiple data types with functional sparse-factor analysis.
    PLoS Comput Biol. 2018;14:e1006520.
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    September 2018
  28. LYU Y, Xue L, Zhang F, Koch H, et al
    Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network.
    PLoS Comput Biol. 2018;14:e1006436.
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    June 2018
  29. SHIN SY, Muller AK, Verma N, Lev S, et al
    Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer.
    PLoS Comput Biol. 2018;14:e1006192.
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    May 2018
  30. RANGAN AV, McGrouther CC, Kelsoe J, Schork N, et al
    A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.
    PLoS Comput Biol. 2018;14:e1006105.
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    February 2018
  31. GHAFFARIZADEH A, Heiland R, Friedman SH, Mumenthaler SM, et al
    PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems.
    PLoS Comput Biol. 2018;14:e1005991.
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    Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification.
    PLoS Comput Biol. 2018;14:e1006026.
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  33. SUN JX, He Y, Sanford E, Montesion M, et al
    A computational approach to distinguish somatic vs. germline origin of genomic alterations from deep sequencing of cancer specimens without a matched normal.
    PLoS Comput Biol. 2018;14:e1005965.
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    January 2018
  34. ENGEL M, Longden J, Ferkinghoff-Borg J, Robin X, et al
    Bowhead: Bayesian modelling of cell velocity during concerted cell migration.
    PLoS Comput Biol. 2018;14:e1005900.
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    November 2017
  35. PATKAR S, Magen A, Sharan R, Hannenhalli S, et al
    A network diffusion approach to inferring sample-specific function reveals functional changes associated with breast cancer.
    PLoS Comput Biol. 2017;13:e1005793.
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    October 2017
  36. GABASOVA E, Reid J, Wernisch L
    Clusternomics: Integrative context-dependent clustering for heterogeneous datasets.
    PLoS Comput Biol. 2017;13:e1005781.
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  37. ROMAN T, Xie L, Schwartz R
    Automated deconvolution of structured mixtures from heterogeneous tumor genomic data.
    PLoS Comput Biol. 2017;13:e1005815.
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    September 2017
  38. DUMEAUX V, Fjukstad B, Fjosne HE, Frantzen JO, et al
    Interactions between the tumor and the blood systemic response of breast cancer patients.
    PLoS Comput Biol. 2017;13:e1005680.
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  39. SOLER-OLIVA ME, Guerrero-Martinez JA, Bachetti V, Reyes JC, et al
    Analysis of the relationship between coexpression domains and chromatin 3D organization.
    PLoS Comput Biol. 2017;13:e1005708.
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