Integrative computational biology for cancer research.
Integrative computational biology for cancer research.
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DOI:
10.1007/s00439-011-0983-z
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发表时间:
2011-10
期刊:
影响因子:
5.3
通讯作者:
Jurisica I
中科院分区:
文献类型:
--
作者:
Fortney K;Jurisica I
Over the past two decades, high-throughput (HTP) technologies such as microarrays and mass spectrometry have fundamentally changed clinical cancer research. They have revealed novel molecular markers of cancer subtypes, metastasis, and drug sensitivity and resistance. Some have been translated into the clinic as tools for early disease diagnosis, prognosis, and individualized treatment and response monitoring. Despite these successes, many challenges remain: HTP platforms are often noisy and suffer from false positives and false negatives; optimal analysis and successful validation require complex workflows; and great volumes of data are accumulating at a rapid pace. Here we discuss these challenges, and show how integrative computational biology can help diminish them by creating new software tools, analytical methods, and data standards. The online version of this article (doi:10.1007/s00439-011-0983-z) contains supplementary material, which is available to authorized users.
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影响因子:
46.9
作者:
Augen, J
通讯作者:
Augen, J
影响因子:
12.3
作者:
Auffray C;Chen Z;Hood L
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Hood L
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作者:
Bamford, S;Dawson, E;Forbes, S;Clements, J;Pettett, R;Dogan, A;Flanagan, A;Teague, J;Futreal, PA;Stratton, MR;Wooster, R
通讯作者:
Wooster, R
DOI:
10.1158/1078-0432.ccr-08-3293
发表时间:
2009-06-01
期刊:
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子:
--
作者:
Agarwal R;Gonzalez-Angulo AM;Myhre S;Carey M;Lee JS;Overgaard J;Alsner J;Stemke-Hale K;Lluch A;Neve RM;Kuo WL;Sorlie T;Sahin A;Valero V;Keyomarsi K;Gray JW;Borresen-Dale AL;Mills GB;Hennessy BT
通讯作者:
Hennessy BT
影响因子:
14.9
作者:
Barnes M;Freudenberg J;Thompson S;Aronow B;Pavlidis P
通讯作者:
Pavlidis P