資源|腫瘤數(shù)據(jù)庫(kù)匯總(收藏級(jí))
日期:2019-08-22 09:44:20
現(xiàn)如今,隨著人們生活方式和環(huán)境的改變,惡性腫瘤已經(jīng)成為疾病死亡病因之一。 傳統(tǒng)化療是對(duì)抗癌癥的常見(jiàn)方法,但它會(huì)攻擊全身,造成不必要的副作用,如脫發(fā),惡心和疲勞。
高通量檢測(cè)技術(shù)迅速發(fā)展,使得與腫瘤相關(guān)的組學(xué)數(shù)據(jù)迅速積累。
除了上述針對(duì)癌癥基因組甲基化的數(shù)據(jù)庫(kù)外,還有一些數(shù)據(jù)庫(kù)搜集和整理更為廣泛的甲基化數(shù)據(jù),如MethDB和NGSmethDB。 MethDB 是較早的DNA甲基化數(shù)據(jù)庫(kù),主要集中于環(huán)境因子對(duì)甲基化的影響; NGSmethDB 基于高通量測(cè)序數(shù)據(jù),最近更新中還包含了SNP信息,以便后續(xù)分析。
蛋白是生命活動(dòng)的主要承擔(dān)者,蛋白結(jié)構(gòu)變異、蛋白修飾的改變以及蛋白含量的變化等導(dǎo)致細(xì)胞的生長(zhǎng)和代謝變化是腫瘤發(fā)生的重要因素。
[1] Samur M K, Yan Z, Wang X, et al. canEvolve: A Web Portal for Integrative Oncogenomics [J]. PLOS ONE, 2013, 8. [2] Gao J, Aksoy B A, Dogrusoz U, et al. Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal [J]. Science Signaling, 2013, 6(269): pl1-pl1. [3] Strausberg R L, Buetow K H, Emmert-Buck M R, et al. The Cancer Genome Anatomy Project: building an annotated gene index [J]. Trends in Genetics Tig, 2000, 16(3): 103-106. [4] Wilks C, Cline M S, Weiler E, et al. The Cancer Genomics Hub (CGHub): overcoming cancer through the power of torrential data [J]. Database, 2014. [5] Zhang J, Finney R P, Rowe W, et al. Systematic analysis of genetic alterations in tumors using Cancer Genome WorkBench (CGWB) [J]. Genome Research, 2007, 17(7): 1111-1117. [6] Forbes S A, Beare D, Gunasekaran P, et al. COSMIC: exploring the world’s knowledge of somatic mutations in human cancer [J]. Nucleic Acids Research, 2015, 43(D1): D805-D811. [7] Banks R, LopezOtín, Carlos. International network of cancer genome projects [J]. Nature, 2010, 464(7291): 993-998. [8] Chang K, Creighton C J, Davis C, et al. The Cancer Genome Atlas Pan-Cancer analysis project [J]. Nature Genetics, 2013, 45(10): 1113-1120. [9] Benz S C, Craft B, Szeto C, et al. The UCSC Cancer Genomics Browser: update 2011 [J]. Nucleic Acids Research, 2013, 43(Database issue): 812-7. [10] Cai H, Gupta S, Rath P, et al. ArrayMap 2014: An updated cancer genome resource [J]. Nucleic Acids Research, 2014, 43(D1). [11] Wu T J, Shamsaddini A, Pan Y, et al. A framework for organizing cancer-related variations from existing databases, publications and NGS data using a High-performance Integrated Virtual Environment (HIVE) [J]. Database, 2014, 2014: bau022-bau022. [12] Scheinin I, Myllykangas S, Borze I, et al. CanGEM: mining gene copy number changes in cancer [J]. Nucleic Acids Research, 2007, 36(Database): D830-D835. [13] Cao Q, Zhou M, Wang X, et al. CaSNP: a database for interrogating copy number alterations of cancer genome from SNP array data [J]. Nucleic Acids Research, 2011, 39(Database issue): D968. [14] Timms B. Cancer genome project to start [J]. European Journal of Cancer, 2000, 36(6): 687. [15] Lv J, Liu H, Su J, et al. DiseaseMeth: a human disease methylation database [J]. Nucleic Acids Research, 2012, 40(Databaseissue): 1030-5. [16] Baek S J, Yang S, Kang T W, et al. MENT: Methylation and expression database of normal and tumor tissues [J]. Gene, 2013, 518(1): 194-200. [17] Huang W Y, Hsu S D, Huang H Y, et al. MethHC: a database of DNA methylation and gene expression in human cancer [J]. Nucleic Acids Research, 2015, 43(D1): D856-D861. [18] He X, Chang S, Zhang J, et al. MethyCancer: the database of human DNA methylation and cancer [J]. Nucleic Acids Research, 2008, 36(Database issue): D836-841. [19] Kolesnikov N, Hastings E, Keays M, et al. ArrayExpress update--simplifying data submissions [J]. Nucleic Acids Research, 2015, 43(D1): D1113-D1116. [20] Frenkel-Morgenstern M, Gorohovski A, Vucenovic D, et al. ChiTaRS 2.1--an improved database of the chimeric transcripts and RNA-seq data with novel sense-antisense chimeric RNA transcripts [J]. Nucleic Acids Research, 2015, 43(D1): D68-D75. [21] Barrett T, Troup D B, Wilhite S E, et al. NCBI GEO: archive for functional genomics data sets - 10years on [J]. Nucleic Acids Research, 2012, 39(D1). [22] Xie B, Ding Q, Han H, et al. miRCancer: a microRNA-cancer association database constructed by text mining on literature [J]. Bioinformatics, 2013, 29(5): 638-644. [23] Rhodes D R, Kalyana-Sundaram S, Mahavisno V, et al. Oncomine 3.0: Genes, Pathways, and Networks in a Collection of 18,000 Cancer Gene Expression Profiles [J]. Neoplasia, 2007, 9(2): 166-180. [24] Wang D, Gu J, Wang T, et al. OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs [J]. Bioinformatics, 2014, 30(15): 2237-2238. [25] Bhattacharya A, Ziebarth J D, Cui Y. SomamiR: A database for somatic mutations impacting microRNA function in cancer [J]. Nucleic Acids Research, 2012, 41(Database issue). [26] Porta-Pardo E, Hrabe T, Godzik A. Cancer3D: understanding cancer mutations through protein structures [J]. Nucleic Acids Research, 2015, 43(D1): D968-D973. [27] Tyagi A, Tuknait A, Anand P, et al. CancerPPD: a database of anticancer peptides and proteins [J]. Nucleic Acids Research, 2015, 43(D1): D837-D843. [28] Li J, Duncan D T, Zhang B. CanProVar: a human cancer proteome variation database [J]. Human Mutation, 2010, 31(3): 219-228. [29] Ellis M J, Gillette M, Carr S A, et al. Connecting genomic alterations to cancer biology with proteomics: The NCI clinical proteomic tumor analysis consortium [J]. Cancer Discovery, 2013, 3(10): 1108-1112. [30] He Y, Zhang M, Ju Y, et al. dbDEPC 2.0: updated database of differentially expressed proteins in human cancers [J]. Nucleic Acids Research, 2012, 40(D1): D964-D971. [31] An O, Pendino V, D’Antonio M, et al. NCG 4.0: the network of cancer genes in the era of massive mutational screenings of cancer genomes [J]. Database, 2014, 2014: bau015-bau015. [32] Leroy B, Fournier J L, Ishioka C, et al. The TP53 website: an integrative resource centre for the TP53 mutation database and TP53 mutant analysis [J]. Nucleic Acids Research, 2013, 41(Database issue): D962. [33] Kumar R, Chaudhary K, Gupta S, et al. CancerDR: Cancer Drug Resistance Database [J]. Scientific Reports, 2013, 3: 1445. [34] Ahmed J, Meinel T, Dunkel M, et al. CancerResource: a comprehensive database of cancer-relevant proteins and compound interactions supported by experimental knowledge [J]. Nucleic Acids Research, 2011, 39(Database issue): 960-7. [35] Bulusu K C, Tym J E, Coker E A, et al. canSAR: updated cancer research and drug discovery knowledgebase [J]. Nucleic Acids Research, 2014, 42(D1): D1040-D1047. [36] Yang W, Soares J, Greninger P, et al. Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells [J]. Nucleic Acids Research, 2013, 41(Database issue): D955. [37] Pires D E V, Blundell T L, Ascher D B. Platinum: A database of experimentally measured effects of mutations on structurally defined protein-ligand complexes [J]. Nucleic Acids Research, 2014, 43(D1).
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