2023南京醫科大學計算機科學與技術考研調劑信息：曹晨教授，2022年2月年起任南京醫科大學生物醫學工程與信息學院教授，博士生導師。1988年生，16年畢業于吉林大學計算機科學與技術學院博士，2017-2021年加拿大卡爾加里大學博士后。

主要從事研究方向是生物信息（計算生物），利用計算機算法/統計方法開發新的生物信息軟件/工具，希望你有科研熱情、努力和一定的編程能力或者生信處理能力，背景需要是統計、計算機、機器學習或者生物信息。現主持國自然青年基金、國自然重點項目（合作單位主持）等項目 。


要求：
本科為雙一流建設高校，研究生成績330+；計算機背景（考試科目是數學+專業課是計算機基礎）或 生物信息背景，

聯系方式： chen.cao@ucalgary.ca

近三年第一作者/通訊作者論文列表如下：
[1] cao c, he j, mak l, perera d, kwok d, wang j, li m, mourier t, gavriliuc s, greenberg m, morrissy s, sycuro l, yang g, jeffares d, long q. reconstruction of microbial haplotypes by integration of statistical and physical linkage in scaffolding, molecular biology and evolution. 2021. doi: 10.1093/molbev/msab037.
[2] cao c, ding b, li q, kwok d, wu j, long q. power analysis of transcriptome-wide association study: implications for practical protocol choice. plos genetics. 2021. doi: 10.1371/journal.pgen.1009405.
[3] cao c, wang j, devin k, cui f, zhang z, zhao d, li j, zou q. webtwas: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study.  nucleic acids research. 2022. doi: https://doi.org/10.1093/nar/gkab957
[4] cao c, mak l, jin g, gordon p, ye k, long q, presm: personalized reference editor for somatic mutation discovery in cancer genomics. bioinformatics. 2019. doi: 10.1093/bioinformatics/bty812.
[5] cao c, kwok d, edie s, li q, ding b, kossinna p, campbell s, wu j, greenberg m, long q. ktwas: integrating kernel machine with transcriptome-wide association studies improves statistical power and reveals novel genes. briefings in bioinformatics. 2020. doi: 10.1093/bib/bbaa270.
[6] cao c, kossinna p, kwok d, qingrun zhang, long q. disentangling genetic feature selection and aggregation in transcriptome-wide association studies[j]. genetics. 2022. doi: 10.1093/genetics/iyab216.
[7] cao c, greenberg m, long. wglink: reconstructing whole-genome viral haplotypes using l0+l1-regularization. bioinformatics. 2021. doi: 10.1093/bioinformatics/btab076.
[8] wei x, wu x, cheng z, wu q, cao c*, xu x*, shang h*, botanical drugs: a new strategy for structure-based target prediction. briefings in bioinformatics. 2021. doi: 10.1093/bib/bbab425.