Packaged: 2020-04-04 07:17:44 UTC; Shawshank

Title: Bacterium and virus analysis of Orthologous Groups (BOG) is a
package for identifying differentially regulated genes in the
Author: Jincheol Park, Cenny Taslim, Shili Lin, The Ohio State
Description: It is designed to identify COG (Cluster of Orthologous
Groups) that are either over or under-represented among genes
that show differential expression under two different
conditions using statistical analysis and graphical

Title: Bacterium and Virus Analysis of Orthologous Groups (BOG) is a
Package for Identifying Differentially Regulated Genes in the
Author: Jincheol Park (Keimyung University, South Korea), Cenny Taslim, Shili Lin (The Ohio State University, USA)
Description: An implementation of three statistical tests for identification of COG (Cluster of Orthologous Groups) that are over represented among genes that show differential expression under conditions. It also provides tabular and graphical summaries of the results for easy visualisation and presentation.

Title: Bayesian Optimal Interval Design for Phase I Clinical Trials
Description: The Bayesian optimal interval (BOIN) design is a novel phase I clinical trial design for finding the maximum tolerated dose (MTD). The BOIN design is motivated by the top priority and concern of clinicians when testing a new drug, which is to effectively treat patients and minimize the chance of exposing them to subtherapeutic or overly toxic doses. The prominent advantage of the BOIN design is that it achieves simplicity and superior performance at the same time. The BOIN design is algorithm-based and can be implemented in a simple way similar to the traditional 3+3 design. The BOIN design yields average performance comparable to the continual reassessment method (CRM, one of the best model-based design) in terms of selecting the MTD, but has a substantially lower risk of assigning patients to subtherapeutic or overly toxic doses.

Description: The Bayesian optimal interval (BOIN) design is a novel phase I clinical trial design for finding the maximum tolerated dose (MTD). The BOIN design is motivated by the top priority and concern of clinicians when testing a new drug, which is to effectively treat patients and minimize the chance of exposing them to subtherapeutic or overly toxic doses. The prominent advantage of the BOIN design is that it achieves simplicity and superior performance at the same time. The BOIN design is algorithm-based and can be implemented in a simple way similar to the traditional 3+3 design. The BOIN design yields an average performance that is comparable to that of the continual reassessment method (CRM, one of the best model-based designs) in terms of selecting the MTD, but has a substantially lower risk of assigning patients to subtherapeutic or overly toxic doses.