Sue Rhee   Department of Plant Biology   Carnegie Institution for Science   260 Panama Street   Stanford, CA 94305   Phone: (650) 325-1521 x251   Fax: (650) 325-6857   Email

People in the Lab
Research Opportunities; Internships
Curriculum Vita (PDF format)
All Publications
Research Statement in 2002
Research Statement in 2005

Two things drive my research these days. One is a desire to uncover the mysteries of how plants process the myriad of information from their environment and reprogram their growth and development. I am fascinated with how plants decide. The other is a desire to uncover the potential for greatness in emerging scientists. I am fascinated with how humans, in particular scientists, decide.

I am trying to engage these two drivers in designing projects to foster the diverse interests of individual members of my group, ranging from evolution of pathways to mechanisms of gene regulation, and to capitalize on the diverse training backgrounds in the group, ranging from molecular biology to physics.

Naturally this network of inspiration lends itself to projects that can be described as a series of Venn diagrams where the intersections represent collaborative and integrative projects among the members. I believe that the union will help satisfy the two driving forces of my research program. Also turnover of lab members over time serves as natural check points and selective forces on the evolution of our collective knowledge and expertise.

We employ several methods in our quest: 1) combination of computational modeling and targeted experimental testing in the lab; 2) systematic collection of large-scale data needed for the modeling through collaboration with other labs; 3) robust, quantitative analysis of the data and the models.

Here are examples of the ‘intersecting’ projects in our group to illustrate the types of questions we are asking and approaches we are taking.

• The quest for novel biological processes

• Systematic discovery of the role of protein degradation in response to the environment

• Exploring the power of metabolomics in dissecting genetic interactions

• Systematic discovery of signaling pathways and complexes

• Genome-wide gene association network (AraNet)

• Network-guided reverse genetic screening

• Automated metabolic network generation from a set of protein sequences

• Discovering missing links in gene expression clusters

I expect that many of the current projects will leave along with the lab members to establish their own groups. I am humbled by so many intriguing, unsolved problems in plant biology and am brewing some concrete ideas about the following topics currently, which may or may not become major projects in my group in the next several years. 

• Systematic discovery of novel reactions and pathways

• Determining the “key” players in functional modules

• Elucidation of the mechanism of connection between exogenous and endogenous signals for growth and development

My group has two types of trainees: postdoctoral researchers who are in their last leg of training before launching their own groups or establishing independence in other ways, and research assistants who typically come right after college or a masters program without much, if any, research experience. Besides these opposite ends of the training spectrum, everyone has his or her unique personality, style of learning, and background. So I try to adjust the style and type of training according to the individual.

In general, my style is to give as much independence and freedom on establishing problems, outlining approaches, designing and executing experiments and interpreting results. Depending on the level of need, I help out in all of these aspects. I meet with each member weekly and we have a weekly group meeting where each person rotates in presenting their work to get feedback from the group. The individual meetings are almost always driven by the individual and he or she decides what to discuss with me and what sort of feedback they’re looking for. I almost never approach the individual to ask what is going on, but rather have an open door policy. Basically I leave people alone, but am cognizant of the scientific questions they’re asking and the problems they’re facing.

Besides training people in the science, I consider training of the scientist to be equally important. I value and try to foster qualities such as intellectual generosity, intellectual integrity, creativity and vision. I believe these qualities distinguish a great scientist from a good scientist. Intellectual generosity does not merely stop at being generous in sharing results and reagents, but also ideas, constructive criticisms and empathy in other people’s problems. The best way to learn this, in my view, is by examples from role models. I am surrounded by colleagues and mentors with many of these qualities and I encourage people in my group to seek, recognize and appreciate such qualities in their peers, advisors, mentors and other scientists. Intellectual integrity is another quality I emphasize, mostly to the beginning researchers. When one is starting out in designing and performing experiments, it is very easy for one’s enthusiasm to overshadow the absolute objectivity required. I see this time and again where if students are aware of the expected result, they tend not to ‘see’ the unexpected result. I am sure this behavior is not always conscious. But that makes it even more critical to emphasize intellectual honesty. I also believe there are ways of fostering creativity and vision, but will not dwell on these further here.

As a Carnegie Scientist, I am not obliged to teach. Nonetheless, our department’s affiliation to the Biological Sciences department of Stanford encouraged me to start teaching seminar courses for incoming undergraduates. Starting spring of 2010, I will teach a seminar called “Networks in Biology” (BIO39N). The course description is as follows:

Networks are everywhere: Friendship links on Facebook, airline routes, power grids, the Internet, the Web, highway systems. The list goes on. Biology is no exception. Food chains, protein interaction maps, metabolic pathways are examples of networks in biology. Despite their ubiquitousness, the study of networks in the real world only started about a decade ago. Exploration and exploitation of network analysis in biological systems is only at its infancy. In this course, we will explore the types of networks in biology and the approaches people are using in studying them through discussions and presentations of original research papers.

The topics we are currently working on are at different stages of the publication process, but none is published yet. As soon as they’re published, I will update this webpage. In the meantime, here are some public websites that contain data that collaborators and my group have been involved in generating, curating and analyzing.

• Plant Metabolic Network

• Plant Metabolomics Consortium

• Associomics Consortium

• The Arabidopsis Information Resource

• Gene Ontology Consortium

1.  Howe D, Costanzo M, Fey P, Gojobori T, Hannick L, Hide W, Hill DP, Kania R, Schaeffer M, St. Pierre S, Twigger S, White O, Rhee SY (2008) The future of biocuration. Nature. 455:47-50.

2. Rhee SY, Wood V, Dolinski K and Draghici S. (2008) Use and Misuse of the Gene Ontology (GO) Annotations. Nature Review Genetics. 9(7):509-15.

3. Lalonde S, Ehrhardt D, Loqué D, Chen J, Rhee SY, and Frommer WB (2008) Molecular and cellular approaches for the detection of protein-protein interactions and generation of protein interaction maps. Plant Journal 53(4):610-35

4. Rhee SY, Dickerson, J, and Xu, D (2006) Bioinformatics and its Applications in Plant Biology. Annual Review of Plant Biology. 57: 335-360

5. Dolan, EL, Soots, BE, Lemaux, PG, Rhee, SY, and Reiser, L (2004) Strategies to Avoid Reinventing the Pre-college Education and Outreach Wheel. Genetics. 166:1601-1609.

6. Bard, JL and Rhee, SY (2004) Ontologies in biology: design, applications and future challenges. Nature Review Genetics 5(3):213-22.

7. Rhee, SY (2004) Carpe Diem. Retooling the Publish or Perish Model into the Share and Survive Model. Plant Physiology. 134(2):543-7.