We have continued to develop our high-density RNAi screening technology, and we have begun to characterize image data from small-scale pilot screens. The ability to quantify image similarity has allowed us to demonstrate that knock-down of genes known to have strong genetic or physical interactions leads to highly similar phenotypes. One of the key objectives was the ability to directly compare the phenotypes resulting from independent screens. Our preliminary data indicates that combining independent screens into a common classifier enables it to more accurately represent more broadly defined phenotypic classes (e.g. blocks in cell cycle stages), while maintaining the very close similarity between phenotypes resulting from knockdown of genes encoding proteins known to physically interact. Work continues on further refinement of this screening platform to achieve a greater degree of consistency and a more universal classifier. We have begun work on a collaboration with Dr. Minoru Ko (LG-NIA) to characterize developmental pathways induced in mouse embryonic stem cells using transcription factor manipulation (1). The first set of pilot experiments will be to drive differentiation along previously known pathways to serve as a set of training controls. We will use WND-CHARM to determine the time course of differentiation for these pathways as well as determine the earliest stages that a specific pathway can be uniquely identified. We have begun work to determine if new phenotypes (or developmental pathways) can be identified by WND-CHARM without them being defined a priori. Preliminary evidence suggests this is possible with very distinct morphologies such as apoptosis, and work is ongoing to investigate if more subtle phenotypic variations can also be discerned. In a published study (2), we were able to demonstrate that WND-CHARM can discern very subtle cellular phenotypes resulting from different mutant alleles of the same gene.
| Shamir, Lior; Rahimi, Salim; Orlov, Nikita et al. (2010) Progression analysis and stage discovery in continuous physiological processes using image computing. EURASIP J Bioinform Syst Biol 2010:107036 |
| Shamir, Lior; Ling, Shari; Rahimi, Salim et al. (2009) Biometric identification using knee X-rays. Int J Biom 1:365-370 |
| Shamir, L; Ling, S M; Scott, W et al. (2009) Early detection of radiographic knee osteoarthritis using computer-aided analysis. Osteoarthritis Cartilage 17:1307-12 |
| Shamir, Lior; Eckley, D Mark; Delaney, John et al. (2009) An Image Informatics Method for Automated Quantitative Analysis of Phenotype Visual Similarities. IEEE NIH Life Sci Syst Appl Workshop 2009:96-99 |
| Nishiyama, Akira; Xin, Li; Sharov, Alexei A et al. (2009) Uncovering early response of gene regulatory networks in ESCs by systematic induction of transcription factors. Cell Stem Cell 5:420-33 |
| Shamir, Lior; Ling, Shari M; Scott Jr, William W et al. (2009) Knee x-ray image analysis method for automated detection of osteoarthritis. IEEE Trans Biomed Eng 56:407-15 |
| Shamir, Lior; Wolkow, Catherine A; Goldberg, Ilya G (2009) Quantitative measurement of aging using image texture entropy. Bioinformatics 25:3060-3 |
| Tadeu, Ana Mafalda Baptista; Ribeiro, Susana; Johnston, Josiah et al. (2008) CENP-V is required for centromere organization, chromosome alignment and cytokinesis. EMBO J 27:2510-22 |
