Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks
In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evo...
Saved in:
Published in | Seminars in cancer biology Vol. 30; pp. 30 - 41 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.02.2015
|
Subjects | |
Online Access | Get full text |
ISSN | 1044-579X 1096-3650 1096-3650 |
DOI | 10.1016/j.semcancer.2014.04.013 |
Cover
Abstract | In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions. |
---|---|
AbstractList | In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions. In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the microenvironment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions. In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions.In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions. Abstract In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions. |
Author | Gerlee, Philip Kim, Eunjung Anderson, Alexander R.A. |
Author_xml | – sequence: 1 givenname: Philip surname: Gerlee fullname: Gerlee, Philip email: philip.gerlee@moffitt.org – sequence: 2 givenname: Eunjung surname: Kim fullname: Kim, Eunjung – sequence: 3 givenname: Alexander R.A. orcidid: 0000-0002-2536-4383 surname: Anderson fullname: Anderson, Alexander R.A. email: alexander.anderson@moffitt.org |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24830623$$D View this record in MEDLINE/PubMed https://research.chalmers.se/publication/226967$$DView record from Swedish Publication Index |
BookMark | eNqNkt1u1DAQhSNURH_gFSCX3Oxix46TIFFUKgpIRVwUJMTNyHEmu95m7WAnrfbtO2G7Fa2EqGTJHs2Zb8aac5jsOe8wSV5xNueMqzerecS10c5gmGeMyzmjw8WT5ICzSs2Eytne9JZylhfVz_3kMMYVY6ySXD5L9jNZCqYycZD8-hBss7BukUajO4ypdemWm_bBLwLGaL17m37VfT-pFuj8sOkxHXzaL3fBGKecwzHojq7h2ofL-Dx52uou4ovb-yj5cfbx--nn2fm3T19OT85nRqlsmIm6wUZqwXJe6LKttCx53VRKNNqoNhcUZaWRhcxFXWU1IqpacZmrTNf0oUYcJRdbbrzGfqyhD3atwwa8tkDzow5mCWapuzWGCBGB5YZLmbWgMhQgK5GDbssWaqnbAplSqBVRj7dUQq6xMegG-tw9-P2Ms0tY-CugOUVZcgK8vgUE_3vEOMDaRoNdpx36MQJXeSF4ySpB0pd_97prslsTCd5tBSb4GAO2YOygB9oMtbYdcAaTLWAFd7aAyRbA6PCpvnhQv2vx_8qTbSXSBq8sZaOxSLLGBjQDNN4-gnH8gGE66yz57RI3GFd-DI4MAhxiBgwuJttOruWSHKv-AN7_G_CoEW4AyrUEvQ |
CitedBy_id | crossref_primary_10_1007_s12672_025_02064_7 crossref_primary_10_1177_1073274820946804 crossref_primary_10_1371_journal_pbio_2002930 crossref_primary_10_3390_cancers15153796 crossref_primary_10_1534_genetics_116_193474 crossref_primary_10_1098_rsif_2019_0332 crossref_primary_10_1007_s11831_020_09405_5 crossref_primary_10_2217_pme_15_5 crossref_primary_10_4137_CIN_S19343 crossref_primary_10_1371_journal_pcbi_1007360 crossref_primary_10_1016_j_semcancer_2014_06_005 |
Cites_doi | 10.1093/bioinformatics/bts514 10.1056/NEJMoa1113205 10.1016/j.neucom.2003.10.017 10.1103/PhysRevE.65.021907 10.1038/nrc2329 10.1093/carcin/21.3.485 10.1007/s11538-009-9399-5 10.1016/j.jtbi.2006.12.004 10.1038/nrc3599 10.1038/376307a0 10.1016/S0022-5193(05)80268-1 10.7326/0003-4819-115-11-843 10.1002/glia.20334 10.1016/j.jtbi.2009.03.005 10.1038/nrc3287 10.1038/sj.onc.1210025 10.1186/1471-2105-7-S1-S7 10.1016/j.cell.2013.03.019 10.1016/j.jtbi.2007.01.027 10.1074/jbc.M104391200 10.1002/emmm.201101131 10.1038/nrc3447 10.1007/978-4-431-54394-7_8 10.1158/1078-0432.CCR-09-1070 10.1002/1097-0142(19941201)74:11<2944::AID-CNCR2820741109>3.0.CO;2-F 10.1038/nrc2808 10.1093/imammb/dqi005 10.1016/j.jtbi.2006.06.034 10.1093/carcin/bgp261 10.1038/cddis.2013.249 10.1038/nature03095 10.1056/NEJMoa1103782 10.1073/pnas.0907676107 10.1016/j.cell.2006.09.042 10.1038/nrm2805 10.3934/mbe.2010.7.385 10.1016/S0140-6736(12)60868-X 10.1038/jid.2009.177 10.1016/j.jtbi.2007.10.038 10.1002/int.4550080406 10.1098/rsfs.2013.0020 10.1073/pnas.1203559109 10.1016/j.jtbi.2013.08.016 10.1016/j.biosystems.2008.10.007 10.1111/j.1755-148X.2010.00786.x 10.1038/nrc1276 10.1056/NEJMoa1002011 10.1038/msb.2011.71 10.1038/msb.2011.17 10.1158/0008-5472.CAN-13-1720 10.1016/j.jtbi.2012.07.026 |
ContentType | Journal Article |
Copyright | 2014 Elsevier Ltd Elsevier Ltd Copyright © 2014 Elsevier Ltd. All rights reserved. |
Copyright_xml | – notice: 2014 Elsevier Ltd – notice: Elsevier Ltd – notice: Copyright © 2014 Elsevier Ltd. All rights reserved. |
DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 5PM ADTPV AOWAS F1S |
DOI | 10.1016/j.semcancer.2014.04.013 |
DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic PubMed Central (Full Participant titles) SwePub SwePub Articles SWEPUB Chalmers tekniska högskola |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
DatabaseTitleList | MEDLINE MEDLINE - Academic |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine Anatomy & Physiology |
EISSN | 1096-3650 |
EndPage | 41 |
ExternalDocumentID | oai_research_chalmers_se_05c1442f_62e3_4935_af8f_b4af7e066ea6 PMC4533881 24830623 10_1016_j_semcancer_2014_04_013 S1044579X14000613 1_s2_0_S1044579X14000613 |
Genre | Journal Article Review Research Support, N.I.H., Extramural |
GrantInformation_xml | – fundername: NCI NIH HHS grantid: U01 CA151924 – fundername: NCI NIH HHS grantid: U01CA151924 – fundername: NCI NIH HHS grantid: U54 CA143970 – fundername: NCI NIH HHS grantid: U54 CA113007 |
GroupedDBID | --- --K --M .1- .FO .~1 0R~ 123 1B1 1P~ 1RT 1~. 1~5 4.4 457 4G. 53G 5RE 5VS 7-5 71M 8P~ AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AATTM AAXKI AAXUO AAYWO ABFRF ABGSF ABJNI ABMAC ABUDA ABWVN ABXDB ACDAQ ACGFO ACGFS ACRLP ACRPL ACVFH ADBBV ADCNI ADEZE ADFGL ADMUD ADNMO ADUVX ADVLN AEBSH AEFWE AEHWI AEIPS AEKER AENEX AEUPX AEVXI AFJKZ AFPUW AFRHN AFTJW AFXIZ AGCQF AGHFR AGQPQ AGRDE AGUBO AGYEJ AIEXJ AIGII AIIUN AIKHN AITUG AJUYK AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU APXCP ASPBG AVWKF AXJTR AZFZN BKOJK BLXMC CAG COF CS3 DM4 EBS EFBJH EFKBS EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA HVGLF HX~ HZ~ IH2 IHE J1W KOM LG5 M41 MO0 N9A O-L O9- OAUVE OC~ OO- OZT P-8 P-9 P2P PC. Q38 R2- RNS ROL RPZ SDF SDG SDP SES SEW SPCBC SSU SSZ T5K UDS UNMZH XPP Z5R ZMT ZU3 ~G- 0SF AACTN AFCTW AFKWA AJOXV AMFUW NCXOZ RIG AAIAV ABYKQ AJBFU DOVZS EFLBG AAYXX AGRNS BNPGV CITATION SSH CGR CUY CVF ECM EIF NPM 7X8 5PM ADTPV AOWAS F1S |
ID | FETCH-LOGICAL-c662t-3bded4a30517a8f9a481bd963dac6f5381b28c47453b92beee6b614562ab009d3 |
IEDL.DBID | AIKHN |
ISSN | 1044-579X 1096-3650 |
IngestDate | Thu Aug 21 06:26:54 EDT 2025 Thu Aug 21 14:35:20 EDT 2025 Thu Sep 04 23:11:47 EDT 2025 Mon Jul 21 05:49:13 EDT 2025 Thu Apr 24 22:55:27 EDT 2025 Tue Jul 01 00:25:34 EDT 2025 Fri Feb 23 02:17:49 EST 2024 Sun Feb 23 10:18:42 EST 2025 Tue Aug 26 20:02:23 EDT 2025 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Keywords | Evolution Microenvironment Neural network Drug resistance Genotype to phenotype map |
Language | English |
License | Copyright © 2014 Elsevier Ltd. All rights reserved. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c662t-3bded4a30517a8f9a481bd963dac6f5381b28c47453b92beee6b614562ab009d3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
ORCID | 0000-0002-2536-4383 |
OpenAccessLink | http://doi.org/10.1016/j.semcancer.2014.04.013 |
PMID | 24830623 |
PQID | 1657318093 |
PQPubID | 23479 |
PageCount | 12 |
ParticipantIDs | swepub_primary_oai_research_chalmers_se_05c1442f_62e3_4935_af8f_b4af7e066ea6 pubmedcentral_primary_oai_pubmedcentral_nih_gov_4533881 proquest_miscellaneous_1657318093 pubmed_primary_24830623 crossref_citationtrail_10_1016_j_semcancer_2014_04_013 crossref_primary_10_1016_j_semcancer_2014_04_013 elsevier_sciencedirect_doi_10_1016_j_semcancer_2014_04_013 elsevier_clinicalkeyesjournals_1_s2_0_S1044579X14000613 elsevier_clinicalkey_doi_10_1016_j_semcancer_2014_04_013 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2015-02-01 |
PublicationDateYYYYMMDD | 2015-02-01 |
PublicationDate_xml | – month: 02 year: 2015 text: 2015-02-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | England |
PublicationPlace_xml | – name: England |
PublicationTitle | Seminars in cancer biology |
PublicationTitleAlternate | Semin Cancer Biol |
PublicationYear | 2015 |
Publisher | Elsevier Ltd |
Publisher_xml | – name: Elsevier Ltd |
References | Gerlee, Anderson (bib0160) 2009; 95 Anderson, Quaranta (bib0005) 2008; 8 Haykin (bib0090) 1999 Leung, Engeler, Frank (bib0075) 1990; 1 Kim, Kim, Lee (bib0220) 2010; 363 Craene, Berx (bib0040) 2013; 13 Farin, Suzuki, Weiker, Goldman, Bruce, Canoll (bib0270) 2006; 53 Ferreira, Martins, Vilela (bib0175) 2002; 65 Flaherty, Puzanov, Kim, Ribas, McArthur, Sosman (bib0215) 2010; 363 Cokol, Chua, Tasan, Mutlu, Weinstein, Suzuki (bib0055) 2011; 7 Nelander, Wang, Nilsson, She, Pratilas, Rosen (bib0145) 2008; 4 Ellis, Hicklin (bib0015) 2009; 15 Jörnsten, Abenius, Kling, Schmidt, Johansson, Nordling (bib0250) 2011; 7 Saunders, Simpson, Thompson, Hill, Endo-Munoz, Leggatt (bib0025) 2012; 4 Vohradsky (bib0135) 2001; 276 Gerlee, Anderson (bib0115) 2009; 259 Popławski, Agero, Gens, Swat, Glazier, Anderson (bib0180) 2009; 71 Al-Mamun, Brown, Hossain, Fall, Wagstaff, Bass (bib0150) 2013; 337 Noman, Palafox, Iba (bib0205) 2014 Romero, Arnold (bib0190) 2009; 10 Weaver, Workman, Stormo (bib0290) 1999 Gerlinger, Rowan, Horswell, Larkin, Endesfelder, Gronroos (bib0010) 2012; 366 Cavallaro, Christofori (bib0285) 2004; 4 Zhang, Athale, Deisboeck (bib0070) 2007; 244 Lieberman, Slack, Pandolfi, Chinnaiyan, Agami, Mendell (bib0035) 2013; 153 Hauschild, Grob, Demidov, Jouary, Gutzmer, Millward (bib0230) 2012; 380 Oyama, Okawa, Nakagawa, Takaoka, Andl, Kim (bib0255) 2007; 26 Basanta, Anderson (bib0045) 2013; 3 Scott, Kuhn, Anderson (bib0050) 2012; 12 Smalley (bib0210) 2010; 130 Sawyers (bib0185) 2004; 432 Macklin, Lowengrub (bib0170) 2007; 245 Byrne (bib0060) 2010; 10 Kazmi, Hossain, Phillips, Al-Mamun, Bass (bib0155) 2012; 313 Kreeger, Lauffenburger (bib0030) 2010; 31 Bray (bib0130) 1995; 376 Margolin, Nemenman, Basso, Wiggins, Stolovitzky, Favera (bib0245) 2006; 7 Narayanan, Keedwell, Gamalielsson, Tatineni (bib0140) 2004; 61 Beckman, Schemmann, Yeang (bib0195) 2012; 109 Hill, Lu, Molina, Heiser, Spellman, Speed (bib0240) 2012; 28 Vaira, Fedele, Pyne, Fasoli, Zadra, Bailey (bib0275) 2010; 107 Gerlee, Anderson (bib0110) 2008; 250 Floyd, Lo, Yun, Sullivan, Kornguth (bib0085) 1994; 74 Baxt (bib0080) 1991; 115 Yao (bib0095) 1993; 8 Bray (bib0125) 1990; 143 Vörsmann, Groeber, Walles, Busch, Beissert, Walczak (bib0265) 2013; 4 Holohan, Van Schaeybroeck, Longley, Johnston (bib0020) 2013; 13 Anderson (bib0065) 2005; 22 Chapman, Hauschild, Robert, Haanen, Ascierto, Larkin (bib0225) 2011; 364 Lowe, Lin (bib0280) 2000; 21 Noman, Palafox, Iba (bib0200) 2013; 6 Gerlee, Anderson (bib0105) 2007; 246 Anderson, Weaver, Cummings, Quaranta (bib0165) 2006; 127 Meyer (bib0100) 1998; 3 Gerlee, Anderson (bib0120) 2010; 7 Kim, Rebecca, Fedorenko, Messina, Mathew, Maria-Engler (bib0235) 2013; 73 Brohem, Cardeal, Tiago, Soengas, Barros, Maria-Engler (bib0260) 2011; 24 Cavallaro (10.1016/j.semcancer.2014.04.013_bib0285) 2004; 4 Jörnsten (10.1016/j.semcancer.2014.04.013_bib0250) 2011; 7 Scott (10.1016/j.semcancer.2014.04.013_bib0050) 2012; 12 Al-Mamun (10.1016/j.semcancer.2014.04.013_bib0150) 2013; 337 Gerlee (10.1016/j.semcancer.2014.04.013_bib0120) 2010; 7 Weaver (10.1016/j.semcancer.2014.04.013_bib0290) 1999 Hauschild (10.1016/j.semcancer.2014.04.013_bib0230) 2012; 380 Noman (10.1016/j.semcancer.2014.04.013_bib0200) 2013; 6 Gerlee (10.1016/j.semcancer.2014.04.013_bib0105) 2007; 246 Anderson (10.1016/j.semcancer.2014.04.013_bib0005) 2008; 8 Gerlinger (10.1016/j.semcancer.2014.04.013_bib0010) 2012; 366 Kreeger (10.1016/j.semcancer.2014.04.013_bib0030) 2010; 31 Brohem (10.1016/j.semcancer.2014.04.013_bib0260) 2011; 24 Gerlee (10.1016/j.semcancer.2014.04.013_bib0115) 2009; 259 Saunders (10.1016/j.semcancer.2014.04.013_bib0025) 2012; 4 Baxt (10.1016/j.semcancer.2014.04.013_bib0080) 1991; 115 Lieberman (10.1016/j.semcancer.2014.04.013_bib0035) 2013; 153 Yao (10.1016/j.semcancer.2014.04.013_bib0095) 1993; 8 Vörsmann (10.1016/j.semcancer.2014.04.013_bib0265) 2013; 4 Sawyers (10.1016/j.semcancer.2014.04.013_bib0185) 2004; 432 Beckman (10.1016/j.semcancer.2014.04.013_bib0195) 2012; 109 Vaira (10.1016/j.semcancer.2014.04.013_bib0275) 2010; 107 Macklin (10.1016/j.semcancer.2014.04.013_bib0170) 2007; 245 Hill (10.1016/j.semcancer.2014.04.013_bib0240) 2012; 28 Flaherty (10.1016/j.semcancer.2014.04.013_bib0215) 2010; 363 Byrne (10.1016/j.semcancer.2014.04.013_bib0060) 2010; 10 Bray (10.1016/j.semcancer.2014.04.013_bib0125) 1990; 143 Kim (10.1016/j.semcancer.2014.04.013_bib0220) 2010; 363 Oyama (10.1016/j.semcancer.2014.04.013_bib0255) 2007; 26 Romero (10.1016/j.semcancer.2014.04.013_bib0190) 2009; 10 Popławski (10.1016/j.semcancer.2014.04.013_bib0180) 2009; 71 Zhang (10.1016/j.semcancer.2014.04.013_bib0070) 2007; 244 Leung (10.1016/j.semcancer.2014.04.013_bib0075) 1990; 1 Margolin (10.1016/j.semcancer.2014.04.013_bib0245) 2006; 7 Floyd (10.1016/j.semcancer.2014.04.013_bib0085) 1994; 74 Kim (10.1016/j.semcancer.2014.04.013_bib0235) 2013; 73 Kazmi (10.1016/j.semcancer.2014.04.013_bib0155) 2012; 313 Craene (10.1016/j.semcancer.2014.04.013_bib0040) 2013; 13 Basanta (10.1016/j.semcancer.2014.04.013_bib0045) 2013; 3 Narayanan (10.1016/j.semcancer.2014.04.013_bib0140) 2004; 61 Gerlee (10.1016/j.semcancer.2014.04.013_bib0160) 2009; 95 Gerlee (10.1016/j.semcancer.2014.04.013_bib0110) 2008; 250 Ferreira (10.1016/j.semcancer.2014.04.013_bib0175) 2002; 65 Nelander (10.1016/j.semcancer.2014.04.013_bib0145) 2008; 4 Lowe (10.1016/j.semcancer.2014.04.013_bib0280) 2000; 21 Vohradsky (10.1016/j.semcancer.2014.04.013_bib0135) 2001; 276 Anderson (10.1016/j.semcancer.2014.04.013_bib0065) 2005; 22 Cokol (10.1016/j.semcancer.2014.04.013_bib0055) 2011; 7 Haykin (10.1016/j.semcancer.2014.04.013_bib0090) 1999 Noman (10.1016/j.semcancer.2014.04.013_bib0205) 2014 Ellis (10.1016/j.semcancer.2014.04.013_bib0015) 2009; 15 Smalley (10.1016/j.semcancer.2014.04.013_bib0210) 2010; 130 Bray (10.1016/j.semcancer.2014.04.013_bib0130) 1995; 376 Chapman (10.1016/j.semcancer.2014.04.013_bib0225) 2011; 364 Farin (10.1016/j.semcancer.2014.04.013_bib0270) 2006; 53 Meyer (10.1016/j.semcancer.2014.04.013_bib0100) 1998; 3 Anderson (10.1016/j.semcancer.2014.04.013_bib0165) 2006; 127 Holohan (10.1016/j.semcancer.2014.04.013_bib0020) 2013; 13 |
References_xml | – volume: 74 start-page: 2944 year: 1994 end-page: 2998 ident: bib0085 article-title: Prediction of breast cancer malignancy using an artificial neural network publication-title: Cancer – volume: 143 start-page: 215 year: 1990 end-page: 231 ident: bib0125 article-title: Intracellular signalling as a parallel distributed process publication-title: J Theor Biol – volume: 22 start-page: 163 year: 2005 end-page: 186 ident: bib0065 article-title: A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion publication-title: Math Med Biol – volume: 250 start-page: 705 year: 2008 end-page: 722 ident: bib0110 article-title: A hybrid cellular automaton model of clonal evolution in cancer: the emergence of the glycolytic phenotype publication-title: J Theor Biol – volume: 259 start-page: 67 year: 2009 end-page: 83 ident: bib0115 article-title: Evolution of cell motility in an individual-based model of tumour growth publication-title: J Theor Biol – volume: 53 start-page: 799 year: 2006 end-page: 808 ident: bib0270 article-title: Transplanted glioma cells migrate and proliferate on host brain vasculature: a dynamic analysis publication-title: Glia – volume: 65 start-page: 1 year: 2002 end-page: 8 ident: bib0175 article-title: Reaction-diffusion model for the growth of avascular tumor publication-title: Phys Rev E – volume: 366 start-page: 883 year: 2012 end-page: 892 ident: bib0010 article-title: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing publication-title: N Engl J Med – volume: 13 start-page: 714 year: 2013 end-page: 726 ident: bib0020 article-title: Cancer drug resistance: an evolving paradigm publication-title: Nat Rev Cancer – volume: 4 start-page: 118 year: 2004 end-page: 132 ident: bib0285 article-title: Cell adhesion and signaling by cadherins and ig-cams in cancer publication-title: Nat Cancer Rev – volume: 432 start-page: 294 year: 2004 end-page: 297 ident: bib0185 article-title: Targeted cancer therapy publication-title: Nature – volume: 246 start-page: 583 year: 2007 end-page: 603 ident: bib0105 article-title: An evolutionary hybrid cellular automaton model of solid tumour growth publication-title: J Theor Biol – volume: 31 start-page: 2 year: 2010 end-page: 8 ident: bib0030 article-title: Cancer systems biology: a network modeling perspective publication-title: Carcinogenesis – volume: 3 year: 2013 ident: bib0045 article-title: Exploiting ecological principles to better understand cancer progression and treatment publication-title: Interface Focus – start-page: 112 year: 1999 end-page: 123 ident: bib0290 article-title: Modeling regulatory networks with weight matrices publication-title: Pac Symp Biocomput – volume: 153 start-page: 9 year: 2013 end-page: 10 ident: bib0035 article-title: Noncoding rnas and cancer publication-title: Cell – volume: 363 year: 2010 ident: bib0220 article-title: Inhibition of mutated braf in melanoma publication-title: N Engl J Med – volume: 95 start-page: 166 year: 2009 end-page: 174 ident: bib0160 article-title: Modelling evolutionary cell behaviour using neural networks: application to tumour growth publication-title: BioSystems – volume: 15 start-page: 7471 year: 2009 end-page: 7478 ident: bib0015 article-title: Resistance to targeted therapies: refining anticancer therapy in the era of molecular oncology publication-title: Clin Cancer Res – volume: 10 start-page: 866 year: 2009 end-page: 876 ident: bib0190 article-title: Exploring protein fitness landscapes by directed evolution publication-title: Nat Rev Mol Cell Biol – year: 2014 ident: bib0205 article-title: Inferring genetic networks with a recurrent neural network model using differential evolution in Springer handbook of bio-/neuroinformatics – volume: 7 start-page: 385 year: 2010 end-page: 400 ident: bib0120 article-title: Diffusion-limited tumour growth: simulations and analysis publication-title: MBE – volume: 13 start-page: 97 year: 2013 end-page: 110 ident: bib0040 article-title: Regulatory networks defining emt during cancer initiation and progression publication-title: Nat Rev Cancer – volume: 376 start-page: 307 year: 1995 end-page: 312 ident: bib0130 article-title: Protein molecules as computational elements in living cells publication-title: Nature – volume: 24 start-page: 35 year: 2011 end-page: 50 ident: bib0260 article-title: Artificial skin in perspective: concepts and applications publication-title: Pigment Cell Melanoma Res – volume: 4 start-page: e719 year: 2013 ident: bib0265 article-title: Development of a human three-dimensional organotypic skin-melanoma spheroid model for in vitro drug testing publication-title: Cell Death Dis – volume: 8 start-page: 227 year: 2008 end-page: 234 ident: bib0005 article-title: Integrative mathematical oncology publication-title: Nat Rev Cancer – volume: 28 start-page: 2804 year: 2012 end-page: 2810 ident: bib0240 article-title: Bayesian inference of signaling network topology in a cancer cell line publication-title: Bioinformatics – volume: 245 start-page: 677 year: 2007 end-page: 704 ident: bib0170 article-title: Nonlinear simulation of the effect of microenvironment on tumor growth publication-title: J Theor Biol – volume: 364 start-page: 2507 year: 2011 end-page: 2516 ident: bib0225 article-title: BRIM-3 Study Group, improved survival with vemurafenib in melanoma with braf v600e mutation publication-title: N Engl J Med – volume: 276 start-page: 36168 year: 2001 end-page: 36173 ident: bib0135 article-title: Neural model of the genetic network publication-title: J Biol Chem – volume: 8 start-page: 539 year: 1993 end-page: 567 ident: bib0095 article-title: Review of evolutionary artificial networks publication-title: Int J Intell Syst – volume: 12 start-page: 445 year: 2012 end-page: 446 ident: bib0050 article-title: Unifying metastasis – integrating intravasation, circulation and end-organ colonization publication-title: Nat Rev Cancer – volume: 1 start-page: 15 year: 1990 end-page: 20 ident: bib0075 article-title: Fingerprint processing using backpropagation neural networks publication-title: Proceedings of the International Joint Conference on Neural Networks I – volume: 7 start-page: 1 year: 2011 end-page: 17 ident: bib0250 article-title: Network modeling of the transcriptional effects of copy number aberrations in glioblastoma publication-title: Mol Syst Biol – volume: 6 start-page: 93 year: 2013 end-page: 103 ident: bib0200 article-title: Reconstruction of Gene regulatory networks from gene expression data using decoupled recurrent neural network model publication-title: Nat Comput Beyond Process Inform Commun Technol – volume: 21 start-page: 485 year: 2000 end-page: 495 ident: bib0280 article-title: Apoptosis in cancer publication-title: Carcinogenesis – volume: 4 start-page: 675 year: 2012 end-page: 684 ident: bib0025 article-title: Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives publication-title: EMBO Mol Med – volume: 7 start-page: S7 year: 2006 ident: bib0245 article-title: Aracne: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context publication-title: BMC Bioinformatics – volume: 313 start-page: 142 year: 2012 end-page: 152 ident: bib0155 article-title: Avascular tumour growth dynamics and the constraints of protein binding for drug transportation publication-title: J Theor Biol – volume: 337 start-page: 150 year: 2013 end-page: 160 ident: bib0150 article-title: A hybrid computational model for the effects of maspin on cancer cell dynamics publication-title: J Theor Biol – volume: 71 start-page: 1189 year: 2009 end-page: 1227 ident: bib0180 article-title: Front instabilities and invasiveness of simulated avascular tumors publication-title: Bull Math Biol – year: 1999 ident: bib0090 article-title: Neural networks: a comprehensive foundation – volume: 130 start-page: 28 year: 2010 end-page: 37 ident: bib0210 article-title: Understanding melanoma signaling networks as the basis for molecular targeted therapy publication-title: J Invest Dermatol – volume: 127 start-page: 905 year: 2006 end-page: 915 ident: bib0165 article-title: Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment publication-title: Cell – volume: 363 start-page: 809 year: 2010 end-page: 819 ident: bib0215 article-title: Inhibition of mutated, activated braf in metastatic melanoma publication-title: N Engl J Med – volume: 26 start-page: 2353 year: 2007 end-page: 2364 ident: bib0255 article-title: Akt induces senescence in primary esophageal epithelial cells but is permissive for differentiation as revealed in organotypic culture publication-title: Oncogene – volume: 61 start-page: 217 year: 2004 end-page: 240 ident: bib0140 article-title: Single-layer artificial neural networks for gene expression analysis publication-title: Neurocomputing – volume: 3 start-page: 2418 year: 1998 end-page: 2423 ident: bib0100 article-title: Evolutionary approaches to neural control in mobile robots publication-title: Syst Man, Cybern – volume: 7 start-page: 1 year: 2011 end-page: 9 ident: bib0055 article-title: Systematic exploration of synergistic drug pairs publication-title: Mol Syst Biol – volume: 107 start-page: 8352 year: 2010 end-page: 8356 ident: bib0275 article-title: Preclinical model of organotypic culture for pharmacodynamic profiling of human tumors publication-title: Proc Natl Acad Sci USA – volume: 115 start-page: 843 year: 1991 end-page: 848 ident: bib0080 article-title: Use of an artificial neural network for the diagnosis of myocardial infarction publication-title: Ann Intern Med – volume: 109 start-page: 14586 year: 2012 end-page: 14591 ident: bib0195 article-title: Impact of genetic dynamics and single-cell heterogeneity on development of nonstandard personalized medicine strategies for cancer publication-title: Proc Natl Acad Sci – volume: 73 start-page: 6874 year: 2013 end-page: 6885 ident: bib0235 article-title: Senescent fibroblasts in melanoma initiation and progression: an integrated theoretical, experimental, and clinical approach publication-title: Cancer Res – volume: 380 start-page: 358 year: 2012 end-page: 365 ident: bib0230 article-title: Dabrafenib in braf-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial publication-title: Lancet – volume: 244 start-page: 96 year: 2007 end-page: 107 ident: bib0070 article-title: Development of a three-dimensional multiscale agent-based tumor model: simulating gene-protein interaction profiles, cell phenotypes and multicellular patterns in brain cancer publication-title: J Theor Biol – volume: 4 year: 2008 ident: bib0145 article-title: Models from experiments: combinatorial drug perturbations of cancer cells publication-title: Mol Syst Biol – volume: 10 start-page: 221 year: 2010 end-page: 230 ident: bib0060 article-title: Dissecting cancer through mathematics: from the cell to the animal model publication-title: Nat Rev Cancer – volume: 28 start-page: 2804 issue: 21 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0240 article-title: Bayesian inference of signaling network topology in a cancer cell line publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts514 – volume: 366 start-page: 883 issue: 10 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0010 article-title: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing publication-title: N Engl J Med doi: 10.1056/NEJMoa1113205 – volume: 61 start-page: 217 year: 2004 ident: 10.1016/j.semcancer.2014.04.013_bib0140 article-title: Single-layer artificial neural networks for gene expression analysis publication-title: Neurocomputing doi: 10.1016/j.neucom.2003.10.017 – volume: 65 start-page: 1 issue: 2 year: 2002 ident: 10.1016/j.semcancer.2014.04.013_bib0175 article-title: Reaction-diffusion model for the growth of avascular tumor publication-title: Phys Rev E doi: 10.1103/PhysRevE.65.021907 – volume: 8 start-page: 227 issue: 3 year: 2008 ident: 10.1016/j.semcancer.2014.04.013_bib0005 article-title: Integrative mathematical oncology publication-title: Nat Rev Cancer doi: 10.1038/nrc2329 – volume: 21 start-page: 485 year: 2000 ident: 10.1016/j.semcancer.2014.04.013_bib0280 article-title: Apoptosis in cancer publication-title: Carcinogenesis doi: 10.1093/carcin/21.3.485 – volume: 71 start-page: 1189 issue: 5 year: 2009 ident: 10.1016/j.semcancer.2014.04.013_bib0180 article-title: Front instabilities and invasiveness of simulated avascular tumors publication-title: Bull Math Biol doi: 10.1007/s11538-009-9399-5 – volume: 245 start-page: 677 issue: 4 year: 2007 ident: 10.1016/j.semcancer.2014.04.013_bib0170 article-title: Nonlinear simulation of the effect of microenvironment on tumor growth publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.12.004 – volume: 13 start-page: 714 issue: 10 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0020 article-title: Cancer drug resistance: an evolving paradigm publication-title: Nat Rev Cancer doi: 10.1038/nrc3599 – volume: 376 start-page: 307 year: 1995 ident: 10.1016/j.semcancer.2014.04.013_bib0130 article-title: Protein molecules as computational elements in living cells publication-title: Nature doi: 10.1038/376307a0 – volume: 143 start-page: 215 year: 1990 ident: 10.1016/j.semcancer.2014.04.013_bib0125 article-title: Intracellular signalling as a parallel distributed process publication-title: J Theor Biol doi: 10.1016/S0022-5193(05)80268-1 – volume: 4 issue: 216 year: 2008 ident: 10.1016/j.semcancer.2014.04.013_bib0145 article-title: Models from experiments: combinatorial drug perturbations of cancer cells publication-title: Mol Syst Biol – volume: 115 start-page: 843 year: 1991 ident: 10.1016/j.semcancer.2014.04.013_bib0080 article-title: Use of an artificial neural network for the diagnosis of myocardial infarction publication-title: Ann Intern Med doi: 10.7326/0003-4819-115-11-843 – volume: 53 start-page: 799 issue: 8 year: 2006 ident: 10.1016/j.semcancer.2014.04.013_bib0270 article-title: Transplanted glioma cells migrate and proliferate on host brain vasculature: a dynamic analysis publication-title: Glia doi: 10.1002/glia.20334 – volume: 259 start-page: 67 issue: 1 year: 2009 ident: 10.1016/j.semcancer.2014.04.013_bib0115 article-title: Evolution of cell motility in an individual-based model of tumour growth publication-title: J Theor Biol doi: 10.1016/j.jtbi.2009.03.005 – volume: 12 start-page: 445 issue: 7 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0050 article-title: Unifying metastasis – integrating intravasation, circulation and end-organ colonization publication-title: Nat Rev Cancer doi: 10.1038/nrc3287 – start-page: 112 year: 1999 ident: 10.1016/j.semcancer.2014.04.013_bib0290 article-title: Modeling regulatory networks with weight matrices publication-title: Pac Symp Biocomput – volume: 26 start-page: 2353 issue: 16 year: 2007 ident: 10.1016/j.semcancer.2014.04.013_bib0255 article-title: Akt induces senescence in primary esophageal epithelial cells but is permissive for differentiation as revealed in organotypic culture publication-title: Oncogene doi: 10.1038/sj.onc.1210025 – year: 2014 ident: 10.1016/j.semcancer.2014.04.013_bib0205 – volume: 7 start-page: S7 issue: Suppl. 1 year: 2006 ident: 10.1016/j.semcancer.2014.04.013_bib0245 article-title: Aracne: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-7-S1-S7 – volume: 153 start-page: 9 issue: 1 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0035 article-title: Noncoding rnas and cancer publication-title: Cell doi: 10.1016/j.cell.2013.03.019 – volume: 246 start-page: 583 issue: 4 year: 2007 ident: 10.1016/j.semcancer.2014.04.013_bib0105 article-title: An evolutionary hybrid cellular automaton model of solid tumour growth publication-title: J Theor Biol doi: 10.1016/j.jtbi.2007.01.027 – volume: 276 start-page: 36168 year: 2001 ident: 10.1016/j.semcancer.2014.04.013_bib0135 article-title: Neural model of the genetic network publication-title: J Biol Chem doi: 10.1074/jbc.M104391200 – volume: 4 start-page: 675 issue: 8 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0025 article-title: Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives publication-title: EMBO Mol Med doi: 10.1002/emmm.201101131 – volume: 3 start-page: 2418 year: 1998 ident: 10.1016/j.semcancer.2014.04.013_bib0100 article-title: Evolutionary approaches to neural control in mobile robots publication-title: Syst Man, Cybern – volume: 13 start-page: 97 issue: 2 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0040 article-title: Regulatory networks defining emt during cancer initiation and progression publication-title: Nat Rev Cancer doi: 10.1038/nrc3447 – volume: 6 start-page: 93 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0200 article-title: Reconstruction of Gene regulatory networks from gene expression data using decoupled recurrent neural network model publication-title: Nat Comput Beyond Process Inform Commun Technol doi: 10.1007/978-4-431-54394-7_8 – volume: 15 start-page: 7471 issue: 24 year: 2009 ident: 10.1016/j.semcancer.2014.04.013_bib0015 article-title: Resistance to targeted therapies: refining anticancer therapy in the era of molecular oncology publication-title: Clin Cancer Res doi: 10.1158/1078-0432.CCR-09-1070 – volume: 74 start-page: 2944 year: 1994 ident: 10.1016/j.semcancer.2014.04.013_bib0085 article-title: Prediction of breast cancer malignancy using an artificial neural network publication-title: Cancer doi: 10.1002/1097-0142(19941201)74:11<2944::AID-CNCR2820741109>3.0.CO;2-F – volume: 10 start-page: 221 issue: 3 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0060 article-title: Dissecting cancer through mathematics: from the cell to the animal model publication-title: Nat Rev Cancer doi: 10.1038/nrc2808 – volume: 22 start-page: 163 issue: 2 year: 2005 ident: 10.1016/j.semcancer.2014.04.013_bib0065 article-title: A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion publication-title: Math Med Biol doi: 10.1093/imammb/dqi005 – volume: 244 start-page: 96 issue: 1 year: 2007 ident: 10.1016/j.semcancer.2014.04.013_bib0070 article-title: Development of a three-dimensional multiscale agent-based tumor model: simulating gene-protein interaction profiles, cell phenotypes and multicellular patterns in brain cancer publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.06.034 – volume: 1 start-page: 15 year: 1990 ident: 10.1016/j.semcancer.2014.04.013_bib0075 article-title: Fingerprint processing using backpropagation neural networks publication-title: Proceedings of the International Joint Conference on Neural Networks I – volume: 31 start-page: 2 issue: 1 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0030 article-title: Cancer systems biology: a network modeling perspective publication-title: Carcinogenesis doi: 10.1093/carcin/bgp261 – volume: 4 start-page: e719 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0265 article-title: Development of a human three-dimensional organotypic skin-melanoma spheroid model for in vitro drug testing publication-title: Cell Death Dis doi: 10.1038/cddis.2013.249 – volume: 432 start-page: 294 issue: 7015 year: 2004 ident: 10.1016/j.semcancer.2014.04.013_bib0185 article-title: Targeted cancer therapy publication-title: Nature doi: 10.1038/nature03095 – volume: 364 start-page: 2507 issue: 26 year: 2011 ident: 10.1016/j.semcancer.2014.04.013_bib0225 article-title: BRIM-3 Study Group, improved survival with vemurafenib in melanoma with braf v600e mutation publication-title: N Engl J Med doi: 10.1056/NEJMoa1103782 – volume: 107 start-page: 8352 issue: 18 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0275 article-title: Preclinical model of organotypic culture for pharmacodynamic profiling of human tumors publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.0907676107 – volume: 127 start-page: 905 year: 2006 ident: 10.1016/j.semcancer.2014.04.013_bib0165 article-title: Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment publication-title: Cell doi: 10.1016/j.cell.2006.09.042 – volume: 10 start-page: 866 issue: 12 year: 2009 ident: 10.1016/j.semcancer.2014.04.013_bib0190 article-title: Exploring protein fitness landscapes by directed evolution publication-title: Nat Rev Mol Cell Biol doi: 10.1038/nrm2805 – volume: 7 start-page: 385 issue: 2 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0120 article-title: Diffusion-limited tumour growth: simulations and analysis publication-title: MBE doi: 10.3934/mbe.2010.7.385 – volume: 380 start-page: 358 issue: 9839 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0230 article-title: Dabrafenib in braf-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial publication-title: Lancet doi: 10.1016/S0140-6736(12)60868-X – volume: 130 start-page: 28 issue: 1 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0210 article-title: Understanding melanoma signaling networks as the basis for molecular targeted therapy publication-title: J Invest Dermatol doi: 10.1038/jid.2009.177 – volume: 250 start-page: 705 issue: 4 year: 2008 ident: 10.1016/j.semcancer.2014.04.013_bib0110 article-title: A hybrid cellular automaton model of clonal evolution in cancer: the emergence of the glycolytic phenotype publication-title: J Theor Biol doi: 10.1016/j.jtbi.2007.10.038 – volume: 8 start-page: 539 year: 1993 ident: 10.1016/j.semcancer.2014.04.013_bib0095 article-title: Review of evolutionary artificial networks publication-title: Int J Intell Syst doi: 10.1002/int.4550080406 – volume: 3 issue: 4 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0045 article-title: Exploiting ecological principles to better understand cancer progression and treatment publication-title: Interface Focus doi: 10.1098/rsfs.2013.0020 – volume: 109 start-page: 14586 issue: 36 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0195 article-title: Impact of genetic dynamics and single-cell heterogeneity on development of nonstandard personalized medicine strategies for cancer publication-title: Proc Natl Acad Sci doi: 10.1073/pnas.1203559109 – volume: 337 start-page: 150 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0150 article-title: A hybrid computational model for the effects of maspin on cancer cell dynamics publication-title: J Theor Biol doi: 10.1016/j.jtbi.2013.08.016 – volume: 95 start-page: 166 issue: 2 year: 2009 ident: 10.1016/j.semcancer.2014.04.013_bib0160 article-title: Modelling evolutionary cell behaviour using neural networks: application to tumour growth publication-title: BioSystems doi: 10.1016/j.biosystems.2008.10.007 – volume: 24 start-page: 35 issue: 1 year: 2011 ident: 10.1016/j.semcancer.2014.04.013_bib0260 article-title: Artificial skin in perspective: concepts and applications publication-title: Pigment Cell Melanoma Res doi: 10.1111/j.1755-148X.2010.00786.x – volume: 4 start-page: 118 year: 2004 ident: 10.1016/j.semcancer.2014.04.013_bib0285 article-title: Cell adhesion and signaling by cadherins and ig-cams in cancer publication-title: Nat Cancer Rev doi: 10.1038/nrc1276 – volume: 363 start-page: 809 issue: 9 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0215 article-title: Inhibition of mutated, activated braf in metastatic melanoma publication-title: N Engl J Med doi: 10.1056/NEJMoa1002011 – volume: 7 start-page: 1 year: 2011 ident: 10.1016/j.semcancer.2014.04.013_bib0055 article-title: Systematic exploration of synergistic drug pairs publication-title: Mol Syst Biol doi: 10.1038/msb.2011.71 – year: 1999 ident: 10.1016/j.semcancer.2014.04.013_bib0090 – volume: 7 start-page: 1 year: 2011 ident: 10.1016/j.semcancer.2014.04.013_bib0250 article-title: Network modeling of the transcriptional effects of copy number aberrations in glioblastoma publication-title: Mol Syst Biol doi: 10.1038/msb.2011.17 – volume: 73 start-page: 6874 issue: 23 year: 2013 ident: 10.1016/j.semcancer.2014.04.013_bib0235 article-title: Senescent fibroblasts in melanoma initiation and progression: an integrated theoretical, experimental, and clinical approach publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-13-1720 – volume: 313 start-page: 142 year: 2012 ident: 10.1016/j.semcancer.2014.04.013_bib0155 article-title: Avascular tumour growth dynamics and the constraints of protein binding for drug transportation publication-title: J Theor Biol doi: 10.1016/j.jtbi.2012.07.026 – volume: 363 issue: 23 year: 2010 ident: 10.1016/j.semcancer.2014.04.013_bib0220 article-title: Inhibition of mutated braf in melanoma publication-title: N Engl J Med |
SSID | ssj0009414 |
Score | 2.1940682 |
SecondaryResourceType | review_article |
Snippet | In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise... Abstract In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to... In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise... |
SourceID | swepub pubmedcentral proquest pubmed crossref elsevier |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 30 |
SubjectTerms | Disease Progression Drug resistance Evolution Evolution, Molecular Genotype Genotype to phenotype map Hematology, Oncology and Palliative Medicine Humans Microenvironment Models, Theoretical Neoplasms Neural network Neural Networks, Computer Phenotype |
Title | Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks |
URI | https://www.clinicalkey.com/#!/content/1-s2.0-S1044579X14000613 https://www.clinicalkey.es/playcontent/1-s2.0-S1044579X14000613 https://dx.doi.org/10.1016/j.semcancer.2014.04.013 https://www.ncbi.nlm.nih.gov/pubmed/24830623 https://www.proquest.com/docview/1657318093 https://pubmed.ncbi.nlm.nih.gov/PMC4533881 https://research.chalmers.se/publication/226967 |
Volume | 30 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3Nb9MwFLe2TkJcEGzAysdkJMQtNPFXkt3KxFQ-tgtMqrhYtuOsRSydSHfgwt_Oe7FTFBU0JKRe0vop7vvwey_5-WdCXkpWl8xZl1Q-84nAULSQxxLrc19jwS18h7Y4V7ML8X4u5zvkpN8Lg7DKuPaHNb1breM3k6jNyfVyOfkEjYSQeTmHFgETMd8le4yXSo7I3vTdh9n5b-5d0VF84_gEBQYwr9ZfOdQvcoNmoqM9zfjfktR2EbqNpRwwjnZZ6vQ-uRfLSzoN_-AB2fHNPjmYNtBaX_2gr2gH-OyepO-TO2fxvfoB-fIG921BFqMt2My3dNnQMF_aAbgCeccxPTNI53BJkdkVH97S9YoiSCxcIIb-kiJDJkyhCfjy9iG5OH37-WSWxFMXEqcUWyfcVr4ShiN5lynq0giobCuI08o4VcP6mFlWOJELyW3JrPdeWcjxYFcDIVxW_BEZNavGHxIqcgcFYO1sKZlQLC28gAJFFSmrubHGjYnq1axdpCTHkzG-6R579lVv7KPRPjqFT8bHJN0IXgdWjttFit6Out90Csukhsxxu2j-J1HfxnBvdaZbplO95ZJjcryRHHj1v932Re9uGmIeX-SYxq9u4HZK5hyJ12DM4-B-GzUwUUAXyHDSA8fcDEA-8eEvzXLR8YqDRXlRZGPyMbjwQCRyTy20W3QH-7QwaZ1KBw05q7VinmtRcqlNXdTaClPnHqpZb9ST_9HBU3IXrmSAyT8jo_X3G_8cqsC1PSK7r39mRzHWfwHHil_3 |
linkProvider | Elsevier |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3Nb9MwFLfGkIALgo2P8mkkxC00sR0n2W1MTAXaXdikiotlO_ZaxNKJdAcu_O28ZydFUUFDQuoljZ9ivQ-_95Kffybkdc58xayxSe0ylwgMRQN5LDGucB4LbuEC2uJETs7Ex3k-3yFH_V4YhFV2a39c08Nq3f0z7rQ5vlwux5-hkRB5Uc2hRcBEzG-QmyLnBeL63v78jfOoRCD4xtEJDh-AvFp3YVG7yAyaiUB6mvG_pajtEnQbSTngGw056vgeudsVl_Qwzv8-2XHNHtk_bKCxvvhB39AA9wzv0ffIrVn3VX2ffHmHu7Ygh9EWLOZaumxonC8N8K1I3XFAZxrJHM4p8rriq1u6XlGEiMULRNCfU-THhCk0EV3ePiBnx-9PjyZJd-ZCYqVk64Sb2tVCc6Tu0qWvtIC6toYorbWVHlbHzLDSigI0bSpmnHPSQIYHq2oI4KrmD8lus2rcY0JFYaH889ZUOROSpaUTUJ7IMmWea6PtiMhezcp2hOR4LsY31SPPvqqNfRTaR6Xwy_iIpBvBy8jJcb1I2dtR9VtOYZFUkDeuFy3-JOraLthblamWqVRtOeSIHGwkBz79b4991bubgojHzzi6casreJzMC460azDmUXS_jRqYKKEHZDjpgWNuBiCb-PBOs1wEVnGwKC_LbESm0YUHIh3z1ELZRTjWp4VJqzS30I4zryRzXImK50r70isjtC8c1LJOyyf_o4OX5PbkdDZV0w8nn56SO3Anj4D5Z2R3_f3KPYd6cG1ehHj_BdZ0YMI |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Bridging+scales+in+cancer+progression%3A+Mapping+genotype+to+phenotype+using+neural+networks&rft.jtitle=Seminars+in+cancer+biology&rft.au=Gerlee%2C+Philip&rft.au=Kim%2C+Eunjung&rft.au=Anderson%2C+Alexander+R.A.&rft.date=2015-02-01&rft.pub=Elsevier+Ltd&rft.issn=1044-579X&rft.eissn=1096-3650&rft.volume=30&rft.spage=30&rft.epage=41&rft_id=info:doi/10.1016%2Fj.semcancer.2014.04.013&rft.externalDocID=S1044579X14000613 |
thumbnail_m | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Fcdn.clinicalkey.com%2Fck-thumbnails%2F1044579X%2FS1044579X14X00088%2Fcov150h.gif |