Python(编程语言)
四胞胎
计算机科学
数据文件
情报检索
化学
数据挖掘
数据库
数据科学
程序设计语言
生物
怀孕
妊娠期
遗传学
标识
DOI:10.1021/acs.orglett.4c03458
摘要
A Python script for the systematic, high-throughput analysis of accurate mass data was developed and tested on more than 3000 Supporting Information (SI) PDFs from Organic Letters. For each SI file, quadruplets of molecular formula, measured ion, e.g., [M + Na]+, and reported calculated and found masses were extracted and analyzed. Interestingly, only 40% of the files containing readable accurate mass data were both internally consistent and in compliance with The ACS Guide to Scholarly Communication. The analysis revealed unexpected errors and provided actionable advice on how to improve data quality.
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