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美國 Bio-IT World  
美國Bio-IT World雜志由國際數(shù)據集團于2001年創(chuàng)辦，目前已有獨立刊物、網站和行業(yè)會議三大業(yè)務部門。作為美國業(yè)內富有影響力的科技雜志，Bio-IT World的讀者遍及美國排名100位生物科技和醫(yī)藥公司的管理層，500所醫(yī)學院和醫(yī)院的專業(yè)人士，行業(yè)供應商，政府組織和研究人員。雜志內容涵蓋生物科技、醫(yī)藥、衛(wèi)生保健、研發(fā)技術產品和服務、行業(yè)應用、政府、學術和科研組織。

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