報告題目：Identification of rhythmic signals in oscillatory systems with applications to chronobiology
報 告 人：Shyamal Peddada 教授 美國匹茲堡大學
報告時間：2019年7月10日下午2:10-2:50
報告地點：數學樓一樓第一報告廳
報告摘要:
There is a growing interest in studying oscillatory systems in a wide range of applications. For example, in pharmacology researchers are interested in understanding circadian clock and estimating the time to peak expression of circadian genes as they may play a critical role in determining optimal time of treatment. Astrophysicists are interested in identifying temporal patterns in the light emitted by stars to classify stars into groups, and so on. In each of these cases, the fundamental and challenging question of interest is to identify components in the oscillatory system that display a rhythmic pattern. In this talk we describe a very simple and yet a very general framework using constrained statistical inference based methods. The resulting methodology is robust to the shape of the pattern, thus the method does not limit to cosine type curves. The resulting methodology is applied to some well-known circadian clock data.
報告人簡介：
Shyamal Peddada自2017年起擔任美國匹茲堡大學公共衛生院生物統計系教授和系主任。他于1983年在美國匹茲堡大學數學系獲得博士學位，在C. R. Rao教授的指導下。在此之前，他是美國國立衛生研究院NIEHS生物統計學和計算生物學分部的高級研究員。Peddada教授為約束統計推斷（參數和非參數），分析微生物組數據和基因表達研究的方法學做出了重要貢獻。他還在各個科學領域做出了重要貢獻，如女性肌瘤的生長，毒理學和毒理基因組學，嬰兒和母體腸道微生物組和表觀遺傳學。他開發的軟件包，用于分析微生物組數據的ANCOM和基因表達研究的ORIOGEN，被研究人員廣泛使用。Peddada教授是美國統計協會傑出統計應用獎的獲得者。他是美國統計協會和國際統計協會的當選會員。他曾擔任JASA的副主編。
