In genome-wide profiling project, researchers usually select many sets of genes (or ESTs) for further investigation based on the computational analyses of the experimental data. For example, a set of genes is selected because they are clustered together based on their mRNA levels. To generate or support biologically meaningful hypotheses, researchers need to selectively and systematically collect information about the genes/ESTs from various sources. For example, huge amount of gene annotations have been accumulated over decades in distributed databases. In addition, there are plenty of online computational tools (e.g., BLAST, TMHMM, MEME, etc.) that can be customized to generate invaluable information complementary to the local computational analyses of researchers. Most web-based databases and computational tools require a direct human involvement. Sometimes, it is extremely difficult, if not impossible, to perform further computational analyses on the collected information. For example, a cellular image often contains large amount of important information that can be easily understood by human but is beyond the capability of existing computational tools. In addition, the computational results are often far from ideal. Therefore, the timely integration and interpretation of the collected information still relies heavily on the sensibility of biologists. However, it is a challenging task to effectively collect and manage various types of information of interest. Researchers often feel overwhelmed by not only vast amount of information but also the great diversity of information types. To facilitate this task, we developed GeneNotes that provides an integrated environment for surfing the Internet, recording information, annotating genes, and retrieving information in the form of text, HTML, image, PDF, word file, and so on.
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