Joel Bader, Ph.D.
Assistant Professor of Biomedical Engineering
Contact Information
Room 201C, Clark Hall, 3400 N. Charles Street
410-516-7417
410-516-5294 (Fax)
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Link to Dr. Bader's Lab Page
Research Interests
Wiring diagrams for cells and organisms
Drosophila melanogaster is a proven model system for many aspects of human biology. The Drosophila genome provides a parts list for the organism, but does not directly indicate how the parts --- genes and proteins --- are wired together. Our lab provided bioinformatics and computational expertise for a large-scale experimental effort to generate a protein wiring diagram for Drosophila. The experiments, conducted by CuraGen Corporation, used the two-hybrid system to map protein interactions for the majority of the fly proteome. Our map contains over 20,000 unique protein-protein interactions that touch over half of the predicted Drosophila proteins. A computational method of rating two-hybrid interaction confidence was developed to refine this draft map to a higher confidence map of 4679 proteins and 4780 interactions. Statistical modeling of the network showed two levels of organization: a short range organization, presumably corresponding to multiprotein complexes and a more global organization, presumably corresponding to inter-complex connections. The network recapitulated known pathways, extended pathways, and uncovered novel pathway components. This map serves as a starting point for a systems biology modeling of multicellular organisms including humans.
Anchoring protein pathways with genetic screens
Drosophila is an important model organism for human biology and disease. Cell-based RNAi screens now enable full-genome assays to identify genes relevant to human disease-related phenotypes and pharmaceutical intervention. Understanding the functional context of genes identified through RNAi loss-of-function assays (RNAi hits) and making quantitative predictions of the behavior of underlying biological pathways are fundamental challenges. Assembling genes identified as RNAi hits into pathways would permit interpretation of the primary data and assist further hypothesis-driven research.
We are working with the Perrimon Lab at Harvard Medical School, which has been funded by the NIH to establish the Drosophila RNAi Screening Center, to enable quantitative predictions of the topology of process-specific biological networks by merging information from full-genome RNAi screens with data from large-scale screens for protein-protein interactions.
We are enhancing existing Drosophila protein-protein interaction databases by developing novel statistical methods that provide quantitative metrics of data quality. Methods to infer interactions from cross-species comparison and network topology will be developed and applied as well.
We are developing algorithms to build computational models of biological networks by starting with genes identified as RNAi hits. Mathematical properties of small-world networks will be employed to assess the statistical significance of the predicted networks, and algorithm performance will be assessed by quantitative metrics and biological relevance.
We are developing algorithms for efficient analysis and visualization of large networks will be developed as part of an open-source R project and Bioconductor infrastructure for bioinformatics and computational biology.
Ultimately, we aim to generate quantitative predictions of cellular pathways that can serve as the input for more detailed quantitative modeling of specific biological processes. Furthermore, due to similarity at the cellular level, pathways identified in Drosophila will be an important step in understanding human biology and disease.
Evolution of biological networks
Biological networks are robust: small perturbations in environmental conditions, and even large perturbations generated by gene mutations and deletions, often have negligible effect on organism fitness. We are interested in understanding how biological networks have evolved to have these properties. We are collaborating with the Boeke lab at the Johns Hopkins School of Medicine to understand evolutionary motifs in genetic interaction networks, which reveal redundancy in biological pathways.
Selected Publications
- Bader JS, Chaudhuri A, Rothberg JM, Chant J 2004 Gaining confidence in high-throughput protein interaction networks. Nat Biotech 22: 78-85
- Giot L, Bader JS, Brouwer C, Chaudhuri A, Kuang B, Li Y, Hao YL, Ooi CE, GodwinB, Vitols E, Vijayadamodar G, Pochart P, Machineni H, Welsh M, Kong Y, Zerhusen B, Malcolm R, Varrone Z, Collis A, Minto M, Burgess S, McDaniel L, Stimpson E, Spriggs F, Williams J, Neurath K, Ioime N, Agee M, Voss E, Furtak K, Renzulli R, Aanensen N, Carrolla S, Bickelhaupt E, Lazovatsky Y, DaSilva A, Zhong J, Stanyon CA, Finley Jr. RL, White KP, Braverman M, Jarvie T, Gold S, Leach M, Knight J, Shimkets RA, McKenna MP, Chant J, Rothberg JM 2003 A protein interaction map of Drosophila melanogaster Science 302: 1727-1736
- Bader JS 2003 Greedily building protein networks with confidence. Bioinformatics. 19: 1869-1874.
- Sham P, Bader JS, Craig I, O'Donovan M, Owen M 2002 Efficient association studies using pooled DNA: promise and pitfalls. Nature Reviews Genetics 3: 862-871
- Bader JS, Deem MW, Hammond RW, Henck SA, Simpson JW, Rotherberg JM 2002 A Brownian-ratchet DNA pump with applications to single-nucleotide polymorphism genotyping. Appl Phys A 74: 1-4
- Bader JS 2001 The relative power of SNPs and haplotypes as genetic markers for association tests. J. S. Bader. Pharmacogenomics 2: 11-24
- Bader JS, Hammond RW, Henck SA, Deem MW, McDermott GA, Bustillo JM, Simpson JW, Mulhern GT, Rothberg JM 1999 DNA transport by a micromachined Brownian ratchet device. Proc Natl Acad Sci USA 96: 13165-13169
- Bader JS, Berne BJ 1996 Solvation energies and electronic spectra in polar, polarizable media - simulation tests of dielectric continuum theory. J Chem Phys 104: 1293-1308
- Bader JS, Berne BJ, Pollack E, Hanggi P 1996 The energy relaxation of a nonlinear oscillator coupled to a linear bath. J Chem Phys 104: 1111-1119
- Bader JS, Berne BJ 1995 The energy-dependent transmission coefficient and the energy distribution of classical particles escaping from a metastable well. J Chem Phys 102: 7953
- Bader JS, Berne BJ, Pollak E 1995 Activated rate processes: The reactive flux method for one-dimensional surface diffusion. J Chem Phys 102: 4037
- Bader JS, Berne BJ 1994 Quantum and classical relaxation rates from classical simulations. J Chem Phys 100: 8359
- Pollak E, Bader JS, Berne BJ, Talkner P 1993 Theory of correlated hops in surface diffusion. Phys Rev Lett 70: 3299
- Bader JS, Chander D 1989 Computer simulation of photochemically induced electron transfer. Chem Phys Lett 157: 501
- Kuharski RA, Bader JS, Chandler D, Sprik M, Impey RW 1988 Molecular model for aqueous ferrous--ferric electron transfer. J Chem Phys 89: 3248
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