TY - GEN
T1 - Automated image analysis of fluorescence microscopic images to identify protein-protein interactions
AU - Venkataraman, Sankar
AU - Morrell-Falvey, Jennifer L.
AU - Doktycz, Mitchel J.
AU - Hairong, Qi
PY - 2005
Y1 - 2005
N2 - The identification of protein-protein interactions along with their spatial and temporal localization is vital data for assigning functional information to proteins. Historically, these data sets obtained from fluorescence microscopy, have been analyzed manually, a process that is both time consuming and tedious. The development of an automated system that can measure the location dynamics of the interaction between two proteins inside a live cell is a high priority. This paper describes an automated image analysis system used to identify the interactions between two proteins of interest fused to either GFP or DIV IVA, a bacterial cell division protein that localizes to the cell poles [1], Upon the induction of DIV 1VA fusion protein expression, the GFP-fusion protein will be recruited to the cell poles if a positive interaction occurs. Advanced image processing and feature extraction algorithms are discussed in detail and a statistical feature set used to quantify the image-based information is developed.
AB - The identification of protein-protein interactions along with their spatial and temporal localization is vital data for assigning functional information to proteins. Historically, these data sets obtained from fluorescence microscopy, have been analyzed manually, a process that is both time consuming and tedious. The development of an automated system that can measure the location dynamics of the interaction between two proteins inside a live cell is a high priority. This paper describes an automated image analysis system used to identify the interactions between two proteins of interest fused to either GFP or DIV IVA, a bacterial cell division protein that localizes to the cell poles [1], Upon the induction of DIV 1VA fusion protein expression, the GFP-fusion protein will be recruited to the cell poles if a positive interaction occurs. Advanced image processing and feature extraction algorithms are discussed in detail and a statistical feature set used to quantify the image-based information is developed.
UR - http://www.scopus.com/inward/record.url?scp=33846912755&partnerID=8YFLogxK
U2 - 10.1109/iembs.2005.1615451
DO - 10.1109/iembs.2005.1615451
M3 - Conference contribution
AN - SCOPUS:33846912755
SN - 0780387406
SN - 9780780387409
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 4437
EP - 4440
BT - Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Y2 - 1 September 2005 through 4 September 2005
ER -