BIOINFORMATICS: INTEGRATION OF PROTEOMICS DATA

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Proteomics in the last few years has received a lot of interest from academia and industry. The field is growing very rapidly and is now going through a transitional period where a leap in technology is needed to allow for the fulfillment of its promise. To this end, many Labpratpry Infrmation Management Systems (LIMS) companies have invested in development of generic systems and are attempting to make them accessible to proteomics laboratories. Other companies have invested in the data mining of genomics/proteomics information to help further our knowledge of how biological systems behave. The resulting software packages are ones that work well within the context they were developed. Unfortunately, laboratories that depend on these packages find that they have to spend a significant amount of their capital in the purchase of many such specialized packages and then a significant effort in integrating them in such a way as to become useful. The ongoing costs are high for academic users and introduction of new high-throughput technologies may be limited by the time required to modify the proteomics LIMS. Very frequently these hybrid systems are not easy to use, are rather inflexible, and often do not meet the expectations of the researchers or analysts. Most importantly, much of the data gathering and linking automation and the post data acquisition automatic processing that could be done is not, mostly because of the range of expertise needed to attack these problems appropriately. The significant development costs and the range of expertise needed gives rise to an inertia effect where these hybrid systems cannot adapt very quickly to changes that occur in this field and the usefulness to the researcher drops over time. In addition to the proprietary nature of these systems, we frequently find that the software vendors turn over rapidly or may no longer support the software package. Our work in functional annotation and development of tools and databases to enable functional annotation of genome data will benefit from the Center for integrative proteomics being proposed. We are specifically interested in developing databases for storing mass spectrometry data, in particular a database called dbMST for storing MS/MS based sequence information determined from mass spectrometry, as well as a database called dbPTM to track post-translational modifications identified from phosphoproteomic analyses. It would be of tremendous help for us to work with your group and your data in making such databases possible. We are also interested in archiving of interaction information generated from your research into BIND format and will work with you to link your software and databases to BIND. We can also provide support to your efforts to build LIMS systems by setting up services like our SeqHound integrated database system. SeqHound provides the supporting bioinformatics database services that are used within the BIND operation, and also at MDS Proteomics. It is freely available under the GNU license, and it will allow you to track experimental sample information in the context of NCBI RefSeq accession numbers as well as several other standard databases of sequence, structure and literature information. In addition, we have several new tools under development that will allow you to put your research efforts into context of the global assembly of functional Proteomics information that we will be collecting, and analyze your own work so that you may publish and communicate novel findings that arise.