I-Ping Tu, Ph.D.

Research Fellow

The Institute of Statistical Science, Academia Sinica


128, Academia Rd. Sec. 2, Taipei 115, Taiwan, R.O.C.
Tel: 886-2-2787-5687
Fax: 886-2-2788-6833
Emai: iping@stat.sinica.edu.tw

 

Research Areas

Statistical Analysis for Biological Image Data, Clustering Analysis, Dimension Reduction, Scan statistics, Sequential Analysis, Statistical Machine learning, Block Chain.

 

 

My CV

updated 2023.11.13

 

Recent Publications

 

Journal Papers

1.          Szu-Chi Chung, Hsin-Hung Lin, Kuen-Phon Wu, Ting-Li Chen, Wei-Hau Chang* and I-Ping Tu* (2022). “ RE2DC: A robust and efficient 2D classifier with visualization for processing massive and heterogeneous cryo-EM data’’. bioRxiv.  https://doi.org/10.1101/2022.11.21.517443

2.          Shih-Chi Luo, Min-Chi Yeh, Yu-Hsiang Lien, Hsin-Yi Yeh, Huei-Lun Siao, I-Ping Tu, Peter Chi and Meng-Chiao Ho*(2023), “A two-stranded RAD51–ADP filament structure unveils the mechanism of filament dynamics in homologous recombination’’. Nature Communication 14,  4993.

3.          Tze Leung Lai, Shao-Hsuan Wang, Szu-Chi Chung, Wei-hau Chang and I-Ping Tu* (2023). “Uncertainty quantification in dynamic image reconstruction with applications to cryo-EM”.  Statistica Sinica 33, 1771-1788.

4.          Wei-hau Chang*, I-Kuen Tsai, Shih-Hsin Huang, Hsin-Hung Lin, Szu-Chi Chung, I-Ping Tu, Steve S.-F. Yu* and Sunney I. Chan* (2021). “Copper centers in the cryo-EM structure of particulate methane monooxygenase reveal the catalytic machinery of methane oxidation”. Journal of the American Chemical Society 143, 9922-9932.

5.          Wei-Hau Chang*, Shih-Hsin Huang, Hsin-Hung Lin, Szu-Chi Chung and I-Ping Tu (2021). “Cryo-EM analyses permit visualization of structural polymorphism of biological macromolecules’’. Frontiers in Bioinformatics 1, 788308.

6.          Shao-Hsuan Wang, Yi-Ching Yao, Wei-Hau Chang and I-Ping Tu* (2021). “Quantification of model bias underlying the phenomenon of Einstein from Noise”. Statistica Sinica 31, 2355-2379.

7.          Szu-Chi Chung, Shao-Hsuan Wang, Po-Yao Niu, Su-Yun Huang, Wei-Hau Chang and I-Ping Tu* (2020). “Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy”. Annals of Mathematical Sciences and Applications 5, 283-316.

8.          Szu-Chi Chung, Hsin-Hung Lin, Po-Yao Niu, Shih-Hsin Huang, I-Ping Tu* and Wei-Hau Chang* (2020). “Pre-pro is a fast pre-processor for single-particle cryo-EM by enhancing 2D classification”. Communications Biology 3, 508

9.          Ren Chen, I-Ping Tu, Kai-Er Chuang, Qin-Xue Lin, Shih-Wei Liao, Wanjiun Lia* (2020). “ Degree of mining power decentralization for proof-of-work based blockchain systems”. IEEE Network 34, 266-271.

10.      I-Ping Tu*, Su-Yun Huang and Dai-Ni Hsieh (2019). “The generalized degrees of freedom of multilinear principal component analysis”. Journal of Multivariate Analysis 173, 26-37.

11.      Jheng-Syong Wu, Cheng-Yu Hung, Tzu-yun Chen, Sam Song-yao Lin, Shu-Yu Lin, I-Ping Tu, Hung-Ta Chen and Wei-Hau Chang* (2019). “Deriving a sub-nanomolar affinity peptide from TAP to enable smFRET analysis of RNA polymerase II complexes”. Methods 159-160, 59-69.

12.      Ting-Li Chen, Dai-Ni Hsieh, Hung Hung, I-Ping Tu*, Pei-Shien Wu, Yi-MingWu, Wei-Hau Chang and Su-Yun Huang (2014). “γ-SUP: a clustering algorithm for cryo-electron microscopy images of asymmetric particles”.  Annals of Applied Statistics 8, 259-285.

13.      I-Ping Tu*, Shao-Hsuan Wang and Yuan-Fu Huang (2013). “Estimating the Occurrence Rate of DNA Palindromes”. Annals of Applied Statistics 7, 1095-1110.

14.      I-Ping Tu (2013). “The Maximum of a Ratchet Scanning Process over a Poisson Random Field”, Statistica Sinica, 23, 1541-1551.

15.      Hung Hung, Pei-Hsien Wu, I-Ping Tu* and Su-Yun Huang (2012). “On Multilinear Principal Component Analysis of Order-Two Tensors”. Biometrika 99,569-583.

16.      Hao-Chih Lee, Bo-Lin Lin, Wei-Hau Chang and I-Ping Tu* (2012). “Towards Automated De-Noising of Single Molecular FRET Data: ADN for smFRET”. Journal of Biomedical Optics, 17.

17.      Hock Peng Chan*, and I-Ping Tu (2011). “Log-linear, Logistic Model Fitting and Local Score Statistics for Cluster Detection with Covariate Adjustments”. Statistics in Medicine, 30, 91-100.

18.      Wei-Hau Chang*, Michael T.-K. Chiu, Chin-Yu Chen, Chi-Fu Yen, Yen-Cheng Lin, Yi-Ping Weng, Ji-Chau Chang, Yi-Min Wu, Holland Cheng, Jianhua Fu, and I-Ping Tu (2010). “Zernike phase plate cryo-electron microscopy facilitates single particle analysis of unstained asymmetric protein complexes” Structure,  18, 17-27.

19.      Chen, Y.-P., Huang, H.-C., and Tu, I.-P.* (2010). "A New Approach for Selecting the Number of Factors". Computational Statistics and Data Analysis, 54, 2990-2998.

20.      Hock Peng Chan*, I-Ping Tu and Nancy Zhang (2009). “Boundary crossing probability computations in the analysis of scan statistics” in Scan Statistics--Theory and Applications, eds J. Glaz and V. Pozdnyakov and S. Wallenstein, Birkhauser.

21.      I-Ping Tu*, Hung Chen, Xin Chen (2009). “An Eigenvector Variability Plot”. Statistica Sinica. 19, 1741-1754.  

22.      I-Ping Tu (2009). “Asymptotic Overshoot for Arithmetic IID Random Variables”. Statistica Sinica, 19, 315-323.

 

Conference Papers

1.          Szu-Chi Chung, Cheng-Yu Hung, Huei-Lun Siao, Hung-Yi Wu, Wei-Hau Chang, I-Ping Tu* (2021), “Cryo-RALib–a modular library for accelerating alignment in cryo-EM”.  IEEE International Conference on Image Processing (ICIP), 225-229.

2.          Szu-Chi Chung, Shao-Hsuan Wang, Cheng-Yu Hung, Wei-Hau Chang, I-Ping Tu* (2021), “rAMI–rapid alignment with moment of inertia for Cryo-EM image processing”, Microscopy and Microanalysis 27, 3216-3218.

3.          Szu-Chi Chung*, Hung-Yi Wu, Wei-Hau Chang, and I-Ping Tu (2021), “Grouping 3D structure conformations using network analysis on 2D cryo-EM projection images”. Focus on Microscopy 2021.

4.          Yu-Jing Lin, Po-Wei Wu, Cheng-Han Hsu, I-Ping Tu and Shih-Wei Liao (2019). “An Evaluation of Bitcoin Address. Classification based on Transaction History Summarization”. In 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 302-310.

5.          Chi-Ning Chou, Yu-Jing Lin, I-Ping Tu and Shih-Wei Liao (2018). “Personalized Difficulty Adjustment for Countering the Double-Spending Attack in Proof-of-Work Consensus Protocols”. In 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 1456-1462.

 

Presentations in 2018

1.      2018.2.17-21 “A Dimension Reduction Method for cryo-EM Image Analysis”. The Computational Methods and Bioinformatics Session of Biophysics Society 2018 meeting. (Invited Speaker).

2.      2018.6.25 “Double Spending Fork Attack in Blockchain”, The Workshop for Blockchains, Probability and Statistics in Modern Financial Markets, Academia Sinica. (Invited Speaker).

3.      2018.6.26, “Statistical Analysis for Cryo-electron Microscopy Images”, Big data in health sciences conference, NHRI, Taipei. (Invited Speaker).

4.      2018.6.30-7.1 “A Model Bias Problem in Cryo-Electron Microscopy Image Analysis”, The Seventh International Biostatistics Workshop of Jilin University, Changchun, China. (Invited Speaker).

5.      2018.7.2-7.5 “A Model Bias Problem in Cryo-Electron Microscopy Image Analysis”, International Chinese Statistical Association China Conference with the Focus on Data Science, Qingdao, China.

6.      2018.9.3 “Einstein from noise and statistical de-nosing”, ASCEM’s Grand Opening Symposium and Workshop, Academia Sinica.

7.      2018.12.28 “ASCEP: A speedy and robust cryo-EM processing platform”, Symposium on Molecular Imaging, Biorhythms, and Quantitative Science in Biomedicine and Public Health, Academia Sinica.

 

Presentations in 2019
  1. 2019.7.26 “Why is it so hard to learn statistics?”, at the library of life science, Academia Sinica.
  2. 2019.8.14 "Statistical Methods for cryo-EM image analysis”, DSSV at Doshisha University, Kyoto, Japan.
  3. 2019.8.26 “Statistical Analysis for cryo-EM Images”, 2019 ONE DAY SYMPOSIUM ON DATA-DRIVEN AND PHYSICS-BASED ANALYTICS, Academia Sinica.
  4. 2019.11.6-7 “Introduction to PCA, KEPCA and its Application to cryo-EM images”, Waseda University –Academia Sinica Data Science Workshop, Tokyo, Japan.
  5. 2019.11.21-23 “A two-stage dimension reduction method and its applications on highly contaminated image sets”, as a keynote speech in the International Symposium on Theories and Methodologies for Large Complex Data, Tsukuba, Japan.

 

Presentations in 2020
  1. 2020.3.9 “Statistical Analysis for cryo-EM Images“, NTU Mathematics Colloquium.
  2. 2020.6.9 “Applications and Extensions of Principal Component Analysis: from a Top to Protein Structure Determination”, Colloquium at Institute of Physics, Academia Sinica.
  3. 2020.10.29 “Two-stage dimension reduction (2SDR) for noisy high-dimensional images and application to Cryogenic Electron Microscopy, invited lecture, NSYSU, The Department of Applied Mathematics.
  4. 2020.12.29 “Two-stage dimension reduction (2SDR) for noisy high-dimensional images and application to Cryogenic Electron Microscopy, 2020 ICCM on line presentation. (Invited Speaker).

Presentations in 2021
  1. 2021.10.20 “Statistical Methods for cryo-EM Image Analysis”, National University of Singapore, Department of Statistics, on line presentation. (Invited Speaker).

Presentations in 2022
  1. 2022.02.19 “Statistical Analysis for Cryo-EM Image Data”, 科技部自然司化學學門暨自然科學及永續研究推展中心化學組舉辦“物理化學小組 2022春季交流研討會”(Invited Speaker).
  2. 2022.04.22 “Our learning experience on Deep Learning in learning the 3D protein structures from cryo-EM images”, IoP Machine Learning workshop (Invited Speaker).
  3. 2022.10.8 “Unintended Lies with Statistics”, 2022 Ethics Course at TIGP, Academia Sinica.
  4. 2022.10.29 “淺談數據vs 科學”, 2022 中研院院區開放，統計所舉辦科普演講。
  5. 2022.12.2 “Garbage in, Einstein out: A Mathematical Study of Einstein from Noise”, OIST (Okinawa Institute of Science and Technology), Japan (Invited Speaker).

Presentations in 2023
  1. 2023.2.24 “Garbage in, Einstein out”, Department of Statistics, George Mason University, VA, USA.
  2. 2023.7.12 “A Robust Empirical Bayesian Model for Weighted Linear Regression: Application to Cryo-EM Analysis”, ISDCS, AS (Invited Speaker).