@@ -243,7 +243,7 @@ year = {1962}

 }

 @article{Ortmann2015,

-  author =        {Ortmann, Christina a. and Kent, David G. and

+  author =        {Ortmann, Christina A. and Kent, David G. and

                    Nangalia, Jyoti and Silber, Yvonne and

                    Wedge, David C. and Grinfeld, Jacob and

                    Baxter, E. Joanna and Massie, Charles E. and

@@ -314,13 +314,13 @@ year = {1962}

 @article{McFarland2014,

+  author = {McFarland, Christopher D and Mirny, Leonid and Korolev, Kirill S},

   title = {A Tug-of-War between Driver and Passenger Mutations in Cancer and Other Adaptive Processes},

   volume = {111},

   issn = {10916490},

   doi = {10.1101/003053},

   number = {42},

   journal = {Proc Natl Acad Sci U S A},

-  author = {McFarland, Christopher and Mirny, Leonid and Korolev, Kirill S.},

   year = {2014},

   pages = {15138--15143},

 }

@@ -424,7 +424,7 @@ year = {1962}

 }

 @phdthesis{McFarland2014-phd,

-  author =        {McFarland, CD},

+  author =        {McFarland, Christopher D},

   school =        {Harvard University},

   title =         {{The role of deleterious passengers in cancer}},

   year =          {2014},

@@ -663,18 +663,18 @@ year = {2007}

 }

 @article{tomlinson_mutation_1996,

+  author = {Tomlinson, I P and Novelli, M R and Bodmer, W F},

   title = {The mutation rate and cancer},

   volume = {93},

   issn = {0027-8424},

   language = {eng},

   number = {25},

   journal = {Proceedings of the National Academy of Sciences of the United States of America},

-  author = {Tomlinson, I. P. and Novelli, M. R. and Bodmer, W. F.},

   month = dec,

   year = {1996},

   pages = {14800--14803},

   pmid = {8962135},

-  pmcid = {PMC26216}

+  pmcid = {PMC26216},

 }

@@ -797,6 +797,7 @@ year = {2007}

 @article{tomlinson1997a,

+  author = {Tomlinson, I P },

   title = {Game-Theory Models of Interactions between Tumour Cells},

   volume = {33},

   issn = {09598049},

@@ -804,10 +805,9 @@ year = {2007}

   journal = {European Journal of Cancer},

   doi = {10.1016/S0959-8049(97)00170-6},

   url = {https://linkinghub.elsevier.com/retrieve/pii/S0959804997001706},

-  author = {Tomlinson, I.P.M.},

   month = aug,

   year = {1997},

-  pages = {1495-1500}

+  pages = {1495-1500},

 }

@@ -1,3 +1,16 @@

+@article{hansen2020a,

+  title = {Modifying {{Adaptive Therapy}} to {{Enhance Competitive Suppression}}},

+  author = {Hansen, Elsa and Read, Andrew F.},

+  year = {2020},

+  journal = {Cancers},

+  volume = {12},

+  number = {12},

+  pages = {3556},

+  publisher = {{Multidisciplinary Digital Publishing Institute}},

+  doi = {10.3390/cancers12123556},

+  url = {https://www.mdpi.com/2072-6694/12/12/3556},

+}

+

 @article{hansen2020b,

   title = {Cancer Therapy: {{Attempt}} Cure or Manage Drug Resistance?},

   shorttitle = {Cancer Therapy},

@@ -12,20 +25,6 @@

   url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/eva.12994},

 }

-@article{hansen2020a,

-  title = {Modifying {{Adaptive Therapy}} to {{Enhance Competitive Suppression}}},

-  author = {Hansen, Elsa and Read, Andrew F.},

-  year = {2020},

-  month = {dec},

-  journal = {Cancers},

-  volume = {12},

-  number = {12},

-  pages = {3556},

-  publisher = {{Multidisciplinary Digital Publishing Institute}},

-  doi = {10.3390/cancers12123556},

-  url = {https://www.mdpi.com/2072-6694/12/12/3556},

-}

-

 @article{Yuan2012,

   title = {An {{Overview}} of {{Population Genetic Data Simulation}}},

@@ -1,3 +1,31 @@

+@article{hansen2020b,

+  title = {Cancer Therapy: {{Attempt}} Cure or Manage Drug Resistance?},

+  shorttitle = {Cancer Therapy},

+  author = {Hansen, Elsa and Read, Andrew F.},

+  year = {2020},

+  journal = {Evolutionary Applications},

+  volume = {13},

+  number = {7},

+  pages = {1660--1672},

+  issn = {1752-4571},

+  doi = {10.1111/eva.12994},

+  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/eva.12994},

+}

+

+@article{hansen2020a,

+  title = {Modifying {{Adaptive Therapy}} to {{Enhance Competitive Suppression}}},

+  author = {Hansen, Elsa and Read, Andrew F.},

+  year = {2020},

+  month = {dec},

+  journal = {Cancers},

+  volume = {12},

+  number = {12},

+  pages = {3556},

+  publisher = {{Multidisciplinary Digital Publishing Institute}},

+  doi = {10.3390/cancers12123556},

+  url = {https://www.mdpi.com/2072-6694/12/12/3556},

+}

+

 @article{Yuan2012,

   title = {An {{Overview}} of {{Population Genetic Data Simulation}}},

@@ -13,7 +41,13 @@

   pmid = {22149682}

 }

-

+@book{Moran,

+title = {Statistical processes of evolutionary theory},

+author = {Moran, Patrick Alfred Pierce},

+publisher = {Oxford University Press},

+isbn = {978-0-198-54343-5},

+year = {1962}

+}

 @book{nowak_evolutionary_2006,

   address = {Cambridge, Mass.},

@@ -929,3 +929,50 @@ volume = {274},

   year = {2013},

   pages = {1056–1062}

 }

+

+

+@article{krug2019,

+  title = {Accessibility Percolation in Random Fitness Landscapes},

+  author = {Krug, Joachim},

+  year = {2019},

+  month = mar,

+  url = {http://arxiv.org/abs/1903.11913},

+  urldate = {2021-04-23},

+  archiveprefix = {arXiv},

+  eprint = {1903.11913},

+  eprinttype = {arxiv},

+  journal = {arXiv:1903.11913 [math, q-bio]},

+}

+

+

+

+@article{orr_population_2002,

+  title = {The Population Genetics of Adaptation: The Adaptation of Dna Sequences},

+  shorttitle = {The Population Genetics of Adaptation},

+  author = {Orr, H. Allen},

+  year = {2002},

+  month = jul,

+  volume = {56},

+  pages = {1317--1330},

+  issn = {0014-3820},

+  doi = {10.1554/0014-3820(2002)056[1317:TPGOAT]2.0.CO;2},

+  url = {http://www.bioone.org/doi/abs/10.1554/0014-3820%282002%29056%5B1317%3ATPGOAT%5D2.0.CO%3B2},

+  journal = {Evolution},

+  number = {7}

+}

+

+

+

+@article{gillespie1984,

+  title = {Molecular {{Evolution Over}} the {{Mutational Landscape}}},

+  author = {Gillespie, John H.},

+  year = {1984},

+  volume = {38},

+  pages = {1116--1129},

+  publisher = {{[Society for the Study of Evolution, Wiley]}},

+  issn = {0014-3820},

+  doi = {10.2307/2408444},

+  url = {https://www.jstor.org/stable/2408444},

+  journal = {Evolution},

+  number = {5}

+}

@@ -645,7 +645,6 @@ year = {2007}

 }

-

 @article{ferretti_measuring_2016,

   title = {Measuring Epistasis in Fitness Landscapes: {{The}} Correlation of Fitness Effects of Mutations},

   volume = {396},

@@ -661,3 +660,272 @@ year = {2007}

 }

+@article {Axelrod2006,

+	author = {Axelrod, Robert and Axelrod, David E. and Pienta, Kenneth J.},

+	title = {Evolution of cooperation among tumor cells},

+	volume = {103},

+	number = {36},

+	pages = {13474--13479},

+	year = {2006},

+	doi = {10.1073/pnas.0606053103},

+	issn = {0027-8424},

+	URL = {http://www.pnas.org/content/103/36/13474},

+	journal = {Proceedings of the National Academy of Sciences}

+}

+

+

+@article{hurlbut2018,

+  title = {Game {{Theoretical Model}} of {{Cancer Dynamics}} with {{Four Cell Phenotypes}}},

+  volume = {9},

+  issn = {2073-4336},

+  number = {3},

+  journal = {Games},

+  doi = {10.3390/g9030061},

+  url = {http://www.mdpi.com/2073-4336/9/3/61},

+  author = {Hurlbut, Elena and Ortega, Ethan and Erovenko, Igor and Rowell, Jonathan},

+  month = sep,

+  year = {2018},

+  pages = {61}

+}

+

+

+@article{wuA2016,

+  title = {Evolutionary Game between Commensal and Pathogenic Microbes in Intestinal Microbiota},

+  volume = {7},

+  issn = {2073-4336},

+  number = {3},

+  journal = {Games},

+  doi = {10.3390/g7030026},

+  url = {https://www.mdpi.com/2073-4336/7/3/26},

+  author = {Amy Wu and David Ross},

+  month = sep,

+  year = {2016},

+}

+

+

+@article{Barton2018,

+  title = {Modeling of breast cancer through evolutionary game theory},

+  volume = {11},

+  issn = {1944-4176},

+  number = {4},

+  journal = {Mathematical Sciences Publishers},

+  doi = {10.2140/involve.2018.11.541},

+  url = {https://msp.org/involve/2018/11-4/p01.xhtml},

+  author = {Barton, K. Y., Smith, C., Rychtář, J. and Sendova, T.},

+  month = jan,

+  year = {2018},

+}

+

+

+@book{Otto2007,

+  address = {Princeton},

+  title = {A Biologist's Guide to Mathematical Modeling in Ecology and Evolution},

+  isbn = {978-1-4008-4091-5},

+  publisher = {{Princeton University Press}},

+  author = {Otto, Sarah P and Day, T.},

+  year = {2007},

+  mendid = {17476}

+}

+

+

+

+@article{gerstung2011,

+  title = {Evolutionary {{Games}} with {{Affine Fitness Functions}}: {{Applications}} to {{Cancer}}},

+  volume = {1},

+  issn = {2153-0785, 2153-0793},

+  shorttitle = {Evolutionary {{Games}} with {{Affine Fitness Functions}}},

+  number = {3},

+  journal = {Dynamic Games and Applications},

+  doi = {10.1007/s13235-011-0029-0},

+  url = {http://link.springer.com/10.1007/s13235-011-0029-0},

+  author = {Gerstung, Moritz and Nakhoul, Hani and Beerenwinkel, Niko},

+  month = sep,

+  year = {2011},

+  pages = {370-385}

+}

+

+

+

+@article{archetti2019,

+  title = {Cooperation among Cancer Cells: Applying Game Theory to Cancer},

+  volume = {19},

+  issn = {1474-175X, 1474-1768},

+  shorttitle = {Cooperation among Cancer Cells},

+  number = {2},

+  journal = {Nature Reviews Cancer},

+  doi = {10.1038/s41568-018-0083-7},

+  url = {http://www.nature.com/articles/s41568-018-0083-7},

+  author = {Archetti, Marco and Pienta, Kenneth J.},

+  month = feb,

+  year = {2019},

+  pages = {110-117}

+}

+

+

+

+@article{tomlinson1997a,

+  title = {Game-Theory Models of Interactions between Tumour Cells},

+  volume = {33},

+  issn = {09598049},

+  number = {9},

+  journal = {European Journal of Cancer},

+  doi = {10.1016/S0959-8049(97)00170-6},

+  url = {https://linkinghub.elsevier.com/retrieve/pii/S0959804997001706},

+  author = {Tomlinson, I.P.M.},

+  month = aug,

+  year = {1997},

+  pages = {1495-1500}

+}

+

+

+

+@incollection{basanta2008,

+  address = {Boston},

+  series = {Modeling and {{Simulation}} in {{Science}}, {{Engineering}} and {{Technology}}},

+  title = {A {{Game Theoretical Perspective}} on the {{Somatic Evolution}} of Cancer},

+  isbn = {978-0-8176-4713-1},

+  booktitle = {Selected {{Topics}} in {{Cancer Modeling}}: {{Genesis}}, {{Evolution}}, {{Immune Competition}}, and {{Therapy}}},

+  publisher = {{Birkh\"auser Boston}},

+  url = {https://doi.org/10.1007/978-0-8176-4713-1_5},

+  author = {Basanta, David and Deutsch, Andreas},

+  year = {2008},

+  pages = {1-16},

+  doi = {10.1007/978-0-8176-4713-1_5}

+}

+

+

+@book{maynardsmith1982,

+  address = {Cambridge},

+  title = {Evolution and the Theory of Games},

+  isbn = {978-0-521-24673-6 978-0-521-28884-2},

+  publisher = {{Cambridge Univ. Press}},

+  author = {Maynard Smith, John Maynard},

+  year = {1982}

+}

+

+

+

+

+@article{doebeli2017,

+  title = {Towards a Mechanistic Foundation of Evolutionary Theory},

+  volume = {6},

+  issn = {2050-084X},

+  journal = {eLife},

+  doi = {10.7554/eLife.23804},

+  url = {https://doi.org/10.7554/eLife.23804},

+  author = {Doebeli, Michael and Ispolatov, Yaroslav and Simon, Burt},

+  editor = {Shou, Wenying},

+  month = feb,

+  year = {2017},

+  pages = {e23804}

+}

+

+@article{tsigelny2007,

+title = {Dynamics of a-synuclein aggregation and inhibition of pore-like oligomer development by b-synuclein},

+volume = {274},

+  issn = {1862-1877},

+  number = {7},

+  journal = {FEBS},

+  doi = {10.1111/j.1742-4658.2007.05733.x},

+  url = {https://febs.onlinelibrary.wiley.com/doi/full/10.1111/j.1742-4658.2007.05733.x},

+  author = {Igor F. Tsigelny  Pazit Bar‐On  Yuriy Sharikov  Leslie Crews  Makoto Hashimoto  Mark A. Miller  Steve H. Keller  Oleksandr Platoshyn  Jason X.‐J. Yuan  Eliezer Masliah},

+  month = mar,

+  year = {2007},

+  pages = {16}

+}

+

+@book{maynardsmith1982,

+  address = {{Cambridge}},

+  title = {Evolution and the Theory of Games},

+  isbn = {978-0-521-24673-6 978-0-521-28884-2},

+  publisher = {{Cambridge Univ. Press}},

+  author = {Maynard Smith, John Maynard},

+  year = {1982}

+}

+

+@article{kaznatcheev2017,

+  title = {Cancer Treatment Scheduling and Dynamic Heterogeneity in Social Dilemmas of Tumour Acidity and Vasculature},

+  volume = {116},

+  issn = {0007-0920, 1532-1827},

+  number = {6},

+  journal = {Br J Cancer},

+  url = {http://www.nature.com/articles/bjc20175},

+  doi = {10.1038/bjc.2017.5},

+  author = {Kaznatcheev, Artem and Vander Velde, Robert and Scott, Jacob G and Basanta, David},

+  month = mar,

+  year = {2017},

+  pages = {785-792}

+}

+

+@article{basanta_investigating_2012,

+  title = {Investigating Prostate Cancer Tumour\textendash{}Stroma Interactions: Clinical and Biological Insights from an Evolutionary Game},

+  volume = {106},

+  copyright = {\textcopyright{} 2011 Nature Publishing Group},

+  issn = {0007-0920},

+  shorttitle = {Investigating Prostate Cancer Tumour\textendash{}Stroma Interactions},

+  number = {1},

+  journal = {Br J Cancer},

+  url = {http://www.nature.com/bjc/journal/v106/n1/full/bjc2011517a.html},

+  doi = {10.1038/bjc.2011.517},

+  author = {Basanta, D. and Scott, J. G. and Fishman, M. N. and Ayala, G. and Hayward, S. W. and Anderson, A. R. A.},

+  month = jan,

+  year = {2012},

+  pages = {174-181}

+}

+

+@article{sartakhti2016,

+  title = {Evolutionary {{Dynamics}} of {{Tumor}}-{{Stroma Interactions}} in {{Multiple Myeloma}}},

+  volume = {11},

+  issn = {1932-6203},

+  number = {12},

+  journal = {PLOS ONE},

+  url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168856},

+  doi = {10.1371/journal.pone.0168856},

+  author = {Sartakhti, Javad Salimi and Manshaei, Mohammad Hossein and Bateni, Soroosh and Archetti, Marco},

+  month = dec,

+  year = {2016},

+  pages = {e0168856}

+}

+

+@article{kerr2002a,

+  title = {Local Dispersal Promotes Biodiversity in a Real-Life Game of Rock-Paper-Scissors},

+  author = {Kerr, Benjamin and Riley, Margaret A. and Feldman, Marcus W. and Bohannan, Brendan J. M.},

+  year = {2002},

+  month = jul,

+  volume = {418},

+  pages = {171--174},

+  issn = {0028-0836},

+  doi = {10.1038/nature00823},

+  journal = {Nature},

+  number = {6894},

+  pmid = {12110887}

+}

+

+@article{PhysRevE,

+  title = {Nonlinear adaptive control of competitive release and chemotherapeutic resistance},

+  author = {Newton, P. K. and Ma, Y.},

+  journal = {Phys. Rev. E},

+  volume = {99},

+  issue = {2},

+  pages = {022404},

+  numpages = {10},

+  year = {2019},

+  month = {Feb},

+  publisher = {American Physical Society},

+  doi = {10.1103/PhysRevE.99.022404},

+  url = {https://link.aps.org/doi/10.1103/PhysRevE.99.022404}

+}

+

+@article{Archetti2013,

+  title = {Evolutionary game theory of growth factor production: implications for tumour heterogeneity and resistance to therapies},

+  volume = {109},

+  issn = {0007-0920},

+  number = {4},

+  journal = {British Journal of Cancer},

+  doi = {10.1038/bjc.2013.336},

+  url = {https://doi.org/10.1038/bjc.2013.336},

+  author = {Archetti, Marco},

+  month = aug,

+  year = {2013},

+  pages = {1056–1062}

+}

@@ -645,3 +645,19 @@ year = {2007}

 }

+

+@article{ferretti_measuring_2016,

+  title = {Measuring Epistasis in Fitness Landscapes: {{The}} Correlation of Fitness Effects of Mutations},

+  volume = {396},

+  issn = {0022-5193},

+  shorttitle = {Measuring Epistasis in Fitness Landscapes},

+  journal = {Journal of Theoretical Biology},

+  doi = {10.1016/j.jtbi.2016.01.037},

+  url = {http://www.sciencedirect.com/science/article/pii/S0022519316000771},

+  author = {Ferretti, Luca and Schmiegelt, Benjamin and Weinreich, Daniel and Yamauchi, Atsushi and Kobayashi, Yutaka and Tajima, Fumio and Achaz, Guillaume},

+  month = may,

+  year = {2016},

+  pages = {132-143}

+}

+

+

@@ -1,3 +1,33 @@

+

+@article{Yuan2012,

+  title = {An {{Overview}} of {{Population Genetic Data Simulation}}},

+  volume = {19},

+  issn = {1066-5277},

+  doi = {10.1089/cmb.2010.0188},

+  number = {1},

+  journal = {Journal of Computational Biology},

+  author = {Yuan, Xiguo and Miller, David J. and Zhang, Junying and Herrington, David and Wang, Yue},

+  year = {2012},

+  pages = {42--54},

+  mendid = {18055},

+  pmid = {22149682}

+}

+

+

+

+@book{nowak_evolutionary_2006,

+  address = {Cambridge, Mass.},

+  title = {Evolutionary Dynamics: Exploring the Equations of Life},

+  isbn = {978-0-674-02338-3},

+  shorttitle = {Evolutionary Dynamics},

+  publisher = {{Belknap Press of Harvard University Press}},

+  author = {Nowak, M. A},

+  year = {2006}

+}

+

+

+

+

 @article{Hothorn_2006,

     title = {A Lego System for Conditional Inference},

     author = {Torsten Hothorn and Kurt Hornik and Mark A. van de Wiel

@@ -113,6 +143,60 @@

 }

+

+@article{Carvajal-Rodriguez2010,

+  title = {Simulation of Genes and Genomes Forward in Time.},

+  volume = {11},

+  issn = {1875-5488},

+  doi = {10.2174/138920210790218007},

+  number = {1},

+  journal = {Current genomics},

+  author = {Carvajal-Rodriguez, Antonio},

+  month = mar,

+  year = {2010},

+  pages = {58--61},

+  mendid = {16487},

+  pmid = {20808525}

+}

+

+

+

+@article{Hoban2011,

+  title = {Computer Simulations: Tools for Population and Evolutionary Genetics.},

+  volume = {13},

+  issn = {1471-0064},

+  doi = {10.1038/nrg3130},

+  number = {2},

+  journal = {Nature reviews. Genetics},

+  author = {Hoban, Sean and Bertorelle, Giorgio and Gaggiotti, Oscar E},

+  month = feb,

+  year = {2011},

+  pages = {110--22},

+  mendid = {16510},

+  pmid = {22230817}

+}

+

+

+

+

+

+@article{ramazzotti_capri_2015,

+  title = {{{CAPRI}}: Efficient Inference of Cancer Progression Models from Cross-Sectional Data},

+  volume = {31},

+  issn = {1367-4811},

+  shorttitle = {{{CAPRI}}},

+  doi = {10.1093/bioinformatics/btv296},

+  number = {18},

+  journal = {Bioinformatics (Oxford, England)},

+  author = {Ramazzotti, Daniele and Caravagna, Giulio and Olde Loohuis, Loes and Graudenzi, Alex and Korsunsky, Ilya and Mauri, Giancarlo and Antoniotti, Marco and Mishra, Bud},

+  month = sep,

+  year = {2015},

+  pages = {3016--3026},

+  pmid = {25971740}

+}

+

+

+

 @article{Korsunsky2014,

   author =        {Korsunsky, Ilya and Ramazzotti, Daniele and

                    Caravagna, Giulio and Mishra, Bud},

@@ -195,6 +279,20 @@

   url =           {http://www.ncbi.nlm.nih.gov/pubmed/20876136},

 }

+

+@article{McFarland2014,

+  title = {A Tug-of-War between Driver and Passenger Mutations in Cancer and Other Adaptive Processes},

+  volume = {111},

+  issn = {10916490},

+  doi = {10.1101/003053},

+  number = {42},

+  journal = {Proc Natl Acad Sci U S A},

+  author = {McFarland, Christopher and Mirny, Leonid and Korolev, Kirill S.},

+  year = {2014},

+  pages = {15138--15143},

+}

+

+

 @article{McFarland2013,

   author =        {McFarland, Christopher D and Korolev, Kirill S and

                    Kryukov, Gregory V and Sunyaev, Shamil R and

@@ -434,6 +532,22 @@ year = {2007}

+@article{szendro_predictability_2013,

+  title = {Predictability of Evolution Depends Nonmonotonically on Population Size},

+  volume = {110},

+  issn = {0027-8424, 1091-6490},

+  doi = {10.1073/pnas.1213613110},

+  number = {2},

+  journal = {Proceedings of the National Academy of Sciences},

+  author = {Szendro, Ivan G. and Franke, Jasper and de Visser, J. Arjan G. M. and Krug, Joachim},

+  month = aug,

+  year = {2013},

+  pages = {571--576},

+  pmid = {23267075}

+}

+

+

+

 @article{szendro_quantitative_2013,

 	title = {Quantitative analyses of empirical fitness landscapes},

@@ -1,4 +1,26 @@

-

+@article{Hothorn_2006,

+    title = {A Lego System for Conditional Inference},

+    author = {Torsten Hothorn and Kurt Hornik and Mark A. van de Wiel

+      and Achim Zeileis},

+    journal = {The American Statistician},

+    year = {2006},

+    volume = {60},

+    number = {3},

+    pages = {257--263},

+  }

+

+@article{Hothorn_2008,

+    title = {Implementing a Class of Permutation Tests: The {coin}

+      Package},

+    author = {Torsten Hothorn and Kurt Hornik and Mark A. van de Wiel

+      and Achim Zeileis},

+    journal = {Journal of Statistical Software},

+    year = {2008},

+    volume = {28},

+    number = {8},

+    pages = {1--23},

+    url = {http://www.jstatsoft.org/v28/i08/},

+}

 @article{Desper1999JCB,

   author =        {Desper, R and Jiang, F and Kallioniemi, O P and

@@ -1,9 +1,6 @@

 @article{Desper1999JCB,

-  address =       {Department of Mathematics, Rutgers University,

-                   Piscataway, New Jersey, USA.

-                   r.desper@dfkz-heidelberg.de},

   author =        {Desper, R and Jiang, F and Kallioniemi, O P and

                    Moch, H and Papadimitriou, C H and Sch\"{a}ffer, A A},

   journal =       {J Comput Biol},

@@ -44,6 +41,21 @@

   url =           {http://projecteuclid.org/euclid.bj/1194625594},

 }

+@article{Farahani2013,

+  author =        {Farahani, H and Lagergren, J},

+  journal =       {PloS one},

+  month =         jan,

+  number =        {6},

+  pages =         {e65773},

+  title =         {{Learning oncogenetic networks by reducing to mixed

+                   integer linear programming.}},

+  volume =        {8},

+  year =          {2013},

+  doi =           {10.1371/journal.pone.0065773},

+  issn =          {1932-6203},

+  url =           {http://www.pubmedcentral.nih.gov/},

+}

+

 @article{Gerstung2009,

   author =        {Gerstung, Moritz and Baudis, Michael and Moch, Holger and

                    Beerenwinkel, Niko},

@@ -55,30 +67,6 @@

                    Bayesian networks.}},

   volume =        {25},

   year =          {2009},

-  abstract =      {MOTIVATION: Cancer is an evolutionary process

-                   characterized by accumulating mutations. However, the

-                   precise timing and the order of genetic alterations

-                   that drive tumor progression remain enigmatic.

-                   RESULTS: We present a specific probabilistic

-                   graphical model for the accumulation of mutations and

-                   their interdependencies. The Bayesian network models

-                   cancer progression by an explicit unobservable

-                   accumulation process in time that is separated from

-                   the observable but error-prone detection of

-                   mutations. Model parameters are estimated by an

-                   Expectation-Maximization algorithm and the underlying

-                   interaction graph is obtained by a simulated

-                   annealing procedure. Applying this method to

-                   cytogenetic data for different cancer types, we find

-                   multiple complex oncogenetic pathways deviating

-                   substantially from simplified models, such as linear

-                   pathways or trees. We further demonstrate how the

-                   inferred progression dynamics can be used to improve

-                   genetics-based survival predictions which could

-                   support diagnostics and prognosis. AVAILABILITY: The

-                   software package ct-cbn is available under a GPL

-                   license on the web site cbg.ethz.ch/software/ct-cbn

-                   CONTACT: moritz.gerstung@bsse.ethz.ch.},

   doi =           {10.1093/bioinformatics/btp505},

   issn =          {1367-4811},

   url =           {http://dx.doi.org/10.1093/bioinformatics/btp505 http://

@@ -99,50 +87,9 @@

   year =          {2011},

   doi =           {10.1371/journal.pone.0027136},

   issn =          {1932-6203},

-  url =           {http://dx.plos.org/10.1371/journal.pone.0027136 http://

-                  www.bsse.ethz.ch/cbg/software/ct-cbn},

+  url =           {http://dx.plos.org/10.1371/journal.pone.0027136},

 }

-@article{FarahaniLagergren2013,

-  author =        {Farahani, Hossein Shahrabi and Lagergren, Jens},

-  journal =       {PloS one},

-  month =         jan,

-  number =        {6},

-  pages =         {e65773},

-  title =         {{Learning oncogenetic networks by reducing to mixed

-                   integer linear programming.}},

-  volume =        {8},

-  year =          {2013},

-  abstract =      {Cancer can be a result of accumulation of different

-                   types of genetic mutations such as copy number

-                   aberrations. The data from tumors are cross-sectional

-                   and do not contain the temporal order of the genetic

-                   events. Finding the order in which the genetic events

-                   have occurred and progression pathways are of vital

-                   importance in understanding the disease. In order to

-                   model cancer progression, we propose Progression

-                   Networks, a special case of Bayesian networks, that

-                   are tailored to model disease progression.

-                   Progression networks have similarities with

-                   Conjunctive Bayesian Networks (CBNs) [1],a variation

-                   of Bayesian networks also proposed for modeling

-                   disease progression. We also describe a learning

-                   algorithm for learning Bayesian networks in general

-                   and progression networks in particular. We reduce the

-                   hard problem of learning the Bayesian and progression

-                   networks to Mixed Integer Linear Programming (MILP).

-                   MILP is a Non-deterministic Polynomial-time complete

-                   (NP-complete) problem for which very good heuristics

-                   exists. We tested our algorithm on synthetic and real

-                   cytogenetic data from renal cell carcinoma. We also

-                   compared our learned progression networks with the

-                   networks proposed in earlier publications. The

-                   software is available on the website

-                   https://bitbucket.org/farahani/diprog.},

-  doi =           {10.1371/journal.pone.0065773},

-  issn =          {1932-6203},

-  url =           {http://www.pubmedcentral.nih.gov/},

-}

 @article{Korsunsky2014,

   author =        {Korsunsky, Ilya and Ramazzotti, Daniele and

@@ -13,26 +13,7 @@

                    comparative genome hybridization data.}},

   volume =        {6},

   year =          {1999},

-  abstract =      {Comparative genome hybridization (CGH) is a

-                   laboratory method to measure gains and losses of

-                   chromosomal regions in tumor cells. It is believed

-                   that DNA gains and losses in tumor cells do not occur

-                   entirely at random, but partly through some flow of

-                   causality. Models that relate tumor progression to

-                   the occurrence of DNA gains and losses could be very

-                   useful in hunting cancer genes and in cancer

-                   diagnosis. We lay some mathematical foundations for

-                   inferring a model of tumor progression from a CGH

-                   data set. We consider a class of tree models that are

-                   more general than a path model that has been

-                   developed for colorectal cancer. We derive a tree

-                   model inference algorithm based on the idea of a

-                   maximum-weight branching in a graph, and we show that

-                   under plausible assumptions our algorithm infers the

-                   correct tree. We have implemented our methods in

-                   software, and we illustrate with a CGH data set for

-                   renal cancer.},

-  issn =          {1066-5277},

+    issn =          {1066-5277},

   url =           {http://view.ncbi.nlm.nih.gov/pubmed/10223663},

 }

@@ -160,8 +141,7 @@

                    https://bitbucket.org/farahani/diprog.},

   doi =           {10.1371/journal.pone.0065773},

   issn =          {1932-6203},

-  url =           {http://www.pubmedcentral.nih.gov/

-  articlerender.fcgi?artid=3683041\&tool=pmcentrez\&rendertype=abstract},

+  url =           {http://www.pubmedcentral.nih.gov/},

 }

 @article{Korsunsky2014,

@@ -196,9 +176,6 @@

   year =          {2015},

   doi =           {10.1056/NEJMoa1412098},

   issn =          {0028-4793},

-  url =           {http://www.nejm.org/doi/abs/10.1056/NEJMoa1412098 http://

-                  www.newscientist.com/article/

-  mg22530094.600-mutation-order-reveals-what-cancer-will-do-next.html\#.VO8Tx1vMLmF},

 }

 @article{Raphael2014a,

@@ -226,32 +203,6 @@

                    evolutionary population dynamics.}},

   volume =        {28},

   year =          {2012},

-  abstract =      {MOTIVATION: Many important aspects of evolutionary

-                   dynamics can only be addressed through simulations.

-                   However, accurate simulations of realistically large

-                   populations over long periods of time needed for

-                   evolution to proceed are computationally expensive.

-                   Mutant can be present in very small numbers and yet

-                   (if they are more fit than others) be the key part of

-                   the evolutionary process. This leads to significant

-                   stochasticity that needs to be accounted for.

-                   Different evolutionary events occur at very different

-                   time scales: mutations are typically much rarer than

-                   reproduction and deaths. RESULTS: We introduce a new

-                   exact algorithm for fast fully stochastic simulations

-                   of evolutionary dynamics that include birth, death,

-                   and mutation events. It produces a significant

-                   speedup compared to the direct stochastic simulations

-                   in a typical case when the population size is large

-                   and the mutation rates are much smaller than birth

-                   and death rates. The algorithm performance is

-                   illustrated by several examples that include

-                   evolution on a smooth and rugged fitness landscape.

-                   We also show how this algorithm can be adapted for

-                   approximate simulations of more complex evolutionary

-                   problems and illustrate it by simulations of a

-                   stochastic competitive growth model. CONTACT: