Kyounghwa Bae | PubMed Health

PubMed2005

Prediction of protein interdomain linker regions by a hidden Markov model.

MOTIVATION: Our aim was to predict protein interdomain linker regions using sequence alone, without requiring known homology. Identifying linker regions will delineate domain boundaries, and can be used to computationally dissect proteins into domains prior to clustering them into families. We developed a hidden Markov model of linker/non-linker sequence regions using a linker index derived from amino acid propensity. We employed an efficient Bayesian estimation of the model using Markov Chain Monte Carlo, Gibbs sampling in particular, to simulate parameters from the posteriors. Our model recognizes sequence data to be continuous rather than categorical, and generates a probabilistic output. RESULTS: We applied our method to a dataset of protein sequences in which domains and interdomain linkers had been delineated using the Pfam-A database. The prediction results are superior to a simpler method that also uses linker index.

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PubMed2004

Gene selection using a two-level hierarchical Bayesian model.

SUMMARY: The fundamental problem of gene selection via cDNA data is to identify which genes are differentially expressed across different kinds of tissue samples (e.g. normal and cancer). cDNA data contain large number of variables (genes) and usually the sample size is relatively small so the selection process can be unstable. Therefore, models which incorporate sparsity in terms of variables (genes) are desirable for this kind of problem. This paper proposes a two-level hierarchical Bayesian model for variable selection which assumes a prior that favors sparseness. We adopt a Markov chain Monte Carlo (MCMC) based computation technique to simulate the parameters from the posteriors. The method is applied to leukemia data from a previous study and a published dataset on breast cancer. SUPPLEMENTARY INFORMATION: http://stat.tamu.edu/people/faculty/bmallick.html.

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PubMedDate not supplied

A descriptive analysis of postimplant dosimetric parameters from Radiation Therapy Oncology Group P0019.

BACKGROUND: To date, there are few descriptive analyses of postimplant dosimetry from multi-institutional clinical trials. The purpose of this report is to describe the postimplant dosimetry achieved in Radiation Therapy Oncology Group (RTOG) 0019. METHODS AND MATERIALS: Patients were treated with external beam radiation therapy (45 Gy/25 fractions) followed by a prostate implant (I-125, prescription dose 108 Gy). Postimplant dosimetric assessment was accomplished by obtaining a CT scan of the prostate 1 month after the date of the implant procedure. Prostate volume was outlined by the first author. Dose-volume histograms were calculated by the Radiologic Physics Center. Four dosimetric quantifiers (DQs) were examined: D90 is the dose (reported as percentage of the prescription dose) received by 90% of the prostate; V100, V150, V200 is the percentage of the prostate volume receiving 100%, 150%, and 200% of the prescription dose, respectively. For the purposes of analysis, institutions were divided into three groups according to accrual (<5, 6-9, 10-12). RESULTS: One hundred thirty-eight patients from 27 institutions were registered in the study. Nineteen patients were excluded from this analysis; 14 who had no data and 5 who were ineligible, leaving 119 for analysis. The mean, median, and range of the four DQs are as follows: D90 105.6%, 106.0%, 57.6-174.8%; V100 89.8%, 92.6%, 11.2-100%; V150 58.4%, 59.6%, 0.9-93.7%; and V200 27.9%, 25.1%, 0.3-85.2%. Statistically significant differences according to institutional accrual were observed for D90 (p = 0.0283) and V200 (p = 0.0075), but not for V100 (p = 0.1534) and V150 (p = 0.0509). CONCLUSIONS: The DQ observed in this multi-institutional prospective study are roughly comparable to series from single institutions with considerable brachytherapy experience. Differences in DQs were observed according to institutional accrual. These data could be used to determine a community standard with respect to postimplant dosimetry.

Brachytherapy↗