Titlebook: Chemoinformatics; Concepts, Methods, a Jürgen Bajorath Book 2004 Humana Press 2004

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書目名稱Chemoinformatics影響因子(影響力)




書目名稱Chemoinformatics影響因子(影響力)學(xué)科排名




書目名稱Chemoinformatics網(wǎng)絡(luò)公開度




書目名稱Chemoinformatics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Chemoinformatics被引頻次




書目名稱Chemoinformatics被引頻次學(xué)科排名




書目名稱Chemoinformatics年度引用




書目名稱Chemoinformatics年度引用學(xué)科排名




書目名稱Chemoinformatics讀者反饋




書目名稱Chemoinformatics讀者反饋學(xué)科排名

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1064-3745 is area—and the current popularity of gene-to-drug or si- lar paradigms—is further reflected by the recent introduction of such terms as “discovery informatics” (3), which takes into account th978-1-61737-459-3978-1-59259-802-1Series ISSN 1064-3745 Series E-ISSN 1940-6029

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Book 2004ant statistical models and descriptors (2). The pharmaceutical focus of many developments and efforts in this area—and the current popularity of gene-to-drug or si- lar paradigms—is further reflected by the recent introduction of such terms as “discovery informatics” (3), which takes into account th

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職業(yè)拳擊手

https://doi.org/10.1007/978-3-319-78649-0ental assumption underlying medicinal chemistry. Dissimilarity, the complement of similarity, also plays a major role in a growing number of applications of molecular diversity in combinatorial chemistry, high-throughput screening, and related fields. How molecular information is represented, called

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Soils, Palaeosols, Calcrete and Karst,t user or by the “bench scientist.” This decision can impact not only the style of tools that are rolled out, but is also a factor in terms of how these tools are delivered to the end users. The system that we outline here was designed for use by the non-expert user. As such, the tools that we discu

外星人

Sunando Bandyopadhyay,Nabendu Sekhar Karroughput-screening data. The chapter will briefly describe current high-throughput-screening practices and will stress how the major constraint on the application of chemoinformatics is often the quality of high-throughput-screening data. Discussion of the NCI dataset and how it differs from most hi