Proteomics Projects
U.S. HUPO Statistical Prote omics Initiative finds strength in numbers As this year’s U.S. HUPO conference drew to a close on March 8, the orga nization’s first official project, the Statistical Proteomics Initiative (SPI), was just gearing up. The final conference session was a minisymposium on statistical issues in proteomics chaired by SPI organizers. Once the U.S. HUPO conference officially ended, however, ~65 intrepid researchers carpooled or walked across Seattle in the rain to the Fred Hutchinson Cancer Research Center (FHCRC) for SPI breakout sessions. Despite scheduling that would have spelled disaster for most gatherings, SPI had a turnout that was even larger than organizers had anticipated. In fact, it was standing room only in the main meeting room, and the three SPI subgroups were forced to spread out into various nooks and crannies of the Arnold Building of the FHCRC to discuss their respective topics. Martin McIntosh, who is the chair of SPI and is at FHCRC, sees the large attendance as an indication that proteomics researchers recognize the importance of statistical variation and uncertainty in the analysis of proteomics data. “The goal of this initial kickoff meeting was to bring together as many representatives of practicing proteomics laboratories as possible to help set the initiative’s agenda and priorities,” he says. In the future, SPI members would like to recruit new quantitative scientists from outside the proteomics realm, he adds. Recruitment and education are major themes for SPI. McIntosh explains that the current model of introducing a numbers guru to a bench biologist and having them exchange files now
and then might work for genomics data, such as those generated by microarray experiments, but not for proteomics. “Computational scientists entered into biological data analysis en masse in the 1990s with the development of genomic arrays, but genomic array data are very easy to explain to someone new to the field,” he says. Proteomics techniques such as MS are not as easy to explain, however. He says that to analyze MS data in a proteomics context really requires a deep understanding of the instrumentation, data structures, basic biochemistry, and bioinformatics. Biologists aren’t off the hook when it comes to education, either. “There needs to be a cross-education,” says McIntosh. “The laboratory scientists need to become more and more skilled in the language of variation in data analysis, and the quantitative scientists need to become more and more skilled at understanding the underlying biological processes that are being measured.” McIntosh says that the first step will be for SPI members to devise a list of well-defined core proteomics problems to which existing statistical tools can be applied; this information will allow newcomers to become more familiar with proteomics data and learn the basics of the field. “Hopefully, within a couple of years, we’ll have the facility so that if highly talented computational scientists decide to enter the field of proteomics, there will be a way for them to enter and rapidly get up to speed,” he says. The next step will be to provide a list of outstanding problems, such as top-down proteomics or phosphopeptide identification, that proteomics investigators don’t know how to solve yet and for which new methods and tools must be developed. To make some headway on these
goals, SPI participants at the breakout sessions divided themselves into three subgroups: experimental design and operations, quantitative approaches, and protein/peptide identification. Members of the subgroups discussed their issues in depth, and most attendees favored the idea of developing tutorials and review articles. An additional subgroup on data resources was created after the meeting in response to participants who felt that a need existed for a special subgroup devoted to seeking out and compiling a list of highly characterized data sets. As with so many of these types of projects, all of the participants are volunteers with busy research careers. Enthusiasm can dwindle if clear goals are not stated or if participants do not feel that they are involved. So, one challenge for SPI will be to keep up the momentum, McIntosh points out. The meeting will be followed up with conference calls that involve the co-chairs of each subgroup, he says. Eventually, these calls will expand to include additional researchers. Also, face-toface SPI meetings will be held at the international HUPO meeting in Korea and at the next U.S. HUPO gathering in Bethesda, Md. In addition, JPR will consider SPI manuscripts for inclusion in an upcoming special issue on statistical and computational proteomics. SPI has had a strong start, and >80 researchers have joined the group so far. There’s still room for additional investigators to join, however. The initiative is under the U.S. HUPO umbrella, but newcomers from any country are welcome. Interested scientists should contact Lori McAndrew at lmcandre@ fhcrc.org or visit www.statisticalpro teomics.org for more information. —Katie Cottingham
Government and Society
Systems biology is on the agenda of EU and U.S. On May 3–4, 2007, funders and researchers from the EU and U.S. met at Tufts University to discuss infrastructure needs for systems biology. According to Frederick Marcus of the European Commission, the goal was to “help to establish strategic priorities for both sides”;
these priorities will provide guidance for developing funding opportunities. Joint EU/U.S. requests for applications probably won’t be issued, but grant announcements formed with input from the workshop discussions could encourage research collaborations between EU and U.S. investigators. Participants conferred about ways to handle data
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generated by proteomics and genomics experiments. For example, data standards and modeling approaches were discussed. Marcus says this workshop was just one of many ongoing efforts by the EU to move the field of systems biology forward. “We’re doing this stuff in a big way,” he says. —Katie Cottingham
