Titlebook: Cancer Cell Lines Part 2; John R. W. Masters,Bernhard Palsson Book 2002 Springer Science+Business Media Dordrecht 2002 biology.brain tumor

武士精神

書目名稱Cancer Cell Lines Part 2影響因子(影響力)




書目名稱Cancer Cell Lines Part 2影響因子(影響力)學科排名




書目名稱Cancer Cell Lines Part 2網(wǎng)絡公開度




書目名稱Cancer Cell Lines Part 2網(wǎng)絡公開度學科排名




書目名稱Cancer Cell Lines Part 2被引頻次




書目名稱Cancer Cell Lines Part 2被引頻次學科排名




書目名稱Cancer Cell Lines Part 2年度引用




書目名稱Cancer Cell Lines Part 2年度引用學科排名




書目名稱Cancer Cell Lines Part 2讀者反饋




書目名稱Cancer Cell Lines Part 2讀者反饋學科排名

exacerbate

,Kaposi’s Sarcoma,us KSHV in most spindle cells in situ, and all established long term cell cultures and cell lines lack the presence of KSHV DNA. The usefulness of these lines to study the pathogenesis of KS is therefore questioned.

印第安人

Breast Cancer,rrent series. Equally important are likely to be engineered cell lines expressing candidate genes of potential importance in the evolution and progression of breast cancer, particularly as these can be studied both in vitro and in vivo in xenograft models.

abstemious

1389-2142 f this series on Human Cell Culture are devoted to these cancer cell lines. The chapters in these first 3 volumes have a common aim. Their purpose is to address 3 questions offundamental importance to the relevanceof human cancer cell lines as model systems of each type of cancer: 1. Do the cell lin

無脊椎

Paired Breast Cancer Cell Lines,ltured, the cell lines retain the properties of their parental tumors for lengthy culture periods and thus provide suitable model systems for biomedical studies of at least one major form of breast cancer.

Obvious

he development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number of published research articles, the number of books,andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering.

Antimicrobial

deriver

使殘廢

P. G. Satyaswaroopn activity by the number of published research articles, the number of books,andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering. One reason for the dramatic growth in Bayesian modeling is the availab- ity of computational algorithms to compute

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