美国 Bio-IT World  
美国Bio-IT World杂志由国际数据集团于2001年创办，目前已有独立刊物、网站和行业会议三大业务部门。作为美国业内富有影响力的科技杂志，Bio-IT World的读者遍及美国排名100位生物科技和医药公司的管理层，500所医学院和医院的专业人士，行业供应商，政府组织和研究人员。杂志内容涵盖生物科技、医药、卫生保健、研发技术产品和服务、行业应用、政府、学术和科研组织。

Bio-IT World provides breaking news, analysis, and opinion on enabling technologies that drive biomedical research and drug development, with emphasis on predictive biology, drug discovery, informatics, personalized medicine, and clinical trials. Bio-IT World focuses on the technologies deployed and strategic decisions made by companies in these areas, and their impact on performance.

As the biopharma industry transforms itself from empirical trial-and-error experimentation to an industry reliant upon information, computation, and prediction of outcomes, technologies such as high-throughput genotyping, microarray analysis, and bioinformatics are providing the means of gathering, interpreting, and analyzing biological, chemical, and clinical data to further drug discovery and development. Bio-IT World covers the latest developments in these fields.

Focus areas include:

Genomic analysis: next-generation sequencing, genome-wide association mapping, and data integration

Discovery informatics: collection, analysis and workflows of compound, microarray, proteomic, imaging, and pre-clinical and clinical data

Systems biology: gene, protein, metabolite, and network/pathway information

Computational modeling: biosimulations of pathways, drug action, and clinical data

Predictiveness: in vitro assays, biomarkers, and animal models

Cheminformatics: structure-based drug design, compound characterization, ADME-Tox, and selectivity

Correlation of biological data: disease diagnosis, patient selection, and drug response

Target data: biological, pathway, interaction, patent, and family

IT infrastructure: grid computing and high-performance computing

Text mining: internal documents and published literature

Semantic web: next-generation data sharing and social networking

Clinical research: electronic data capture, patient recruitment, and adaptive trials

Pharmacogenomics: diagnostics for therapeutics, patient stratification