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The genome-wide protein sequences from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) spp. japonica were clustered into families using sequence similarity and domain-based clustering. The two fundamentally different methods resulted in separate cluster sets with complementary properties to compensate the limitations for accurate family analysis.(More)
About 40% of the proteins encoded in eukaryotic genomes are proteins of unknown function (PUFs). Their functional characterization remains one of the main challenges in modern biology. In this study we identified the PUF encoding genes from Arabidopsis (Arabidopsis thaliana) using a combination of sequence similarity, domain-based, and empirical approaches.(More)
A review of previous experiments on the pitch of vibrato tones and the reasons why a new measurement was needed are given. A method of adjustment was used to find the pitch for tones with center frequencies of 220, 440, 880, and 1500 Hz, with total nominal vibrato widths of 50, 100, and 200 cents, and vibrato rates of 4, 6, and 8 Hz. In one case a complex(More)
Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is the difficulty to pinpoint their much shorter functional sub-features, such as catalytically relevant sequence motifs in enzymes or ligand binding signatures of receptor proteins. To identify(More)
MOTIVATION The ability to accurately measure structural similarities among small molecules is important for many analysis routines in drug discovery and chemical genomics. Algorithms used for this purpose include fragment-based fingerprint and graph-based maximum common substructure (MCS) methods. MCS approaches provide one of the most accurate similarity(More)
Acknowledgments I am deeply grateful to my adviser, Dr. Christian R. Shelton, for his invaluable mentoring. Without his help I would not have been able to complete this dissertation. I thank my committee members: Dr. Lonardi for his technical advise, Dr. Hanne-man for his time and advice with social network analysis, and Dr. Keogh for his generous support(More)
Acknowledgments There are many people to whom I owe many thanks for helping me going through this long process of completing a Ph.D. First and foremost, I would like to express my gratitude to my advisor, Dr. Christian R. Shelton, for his unending support, extremely constructive feedback, excellent supervision, and all the encouragement over the last five(More)