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I-Ping Tu, Ph.D. Research Fellow The
Institute of Statistical Science, Academia Sinica |
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Personal Statement |
My research develops advanced statistical frameworks for extracting structural and chemical information from cryogenic electron microscopy (cryo-EM) data, spanning particle-level image analysis to atom-level signal characterization. At the particle level, we developed statistical methods to quantify model bias arising from the “Einstein-from-noise” phenomenon and introduced RE2DC, a robust and computationally efficient method for classifying heterogeneous cryo-EM particle images, reducing computational complexity from O(N^2) to O(N). At the atomic level, we recently developed a robust hierarchical statistical framework that directly estimates atom-specific signal amplitude and spatial width from experimental cryo- EM maps, together with unstructured covariance estimation to characterize their complex dependence. Building on this foundation, our recent work has begun to exploit the Coulombic nature of cryo-EM maps to interrogate atomic identity, resolvability, and local electrostatic characteristics. My current research seeks to advance this direction by statistically separating overlapping atomic signals to recover weak chemical information that is difficult to resolve directly, ultimately extending cryo-EM from determining atomic coordinates toward quantitative characterization of the chemical interactions underlying molecular function.
In my view, statistics has played an important role in
advancing modern science. Please see my lecture (2022.10.29) “data vs science’’.
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Research Areas |
Hierarchical Bayesian Inference, Robust Statistics, Clustering Analysis, Dimension Reduction, Scan Statistics, Statistical Machine learning, cryo-EM Image Analysis, Block Chain.
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Recent Publications |
Journal Papers
1.
I-Ping Tu*, Shu-Cheng Zheng, Yu-Hsiang Lien, Szu-Han
Lin, Po-Chun Lin and Wei-Hau Chang (2026). “A robust
hierarchical linear model for Cryo-EM map analysis”. Annals of Applied
Statistics (AOAS), accepted.
2.
Jheng-Syong Wu ,
Yu-Chun Lin , Yi-Yu Wei , Hsin-Hung Lin , Yang-Chih Liu , Jen-Wei Chang , I-Ping Tu, Hung-Ta Chen* and
Wei-Hau Chang* (2026). "Dynamic positioning of
Rpc34 winged-helix in RNA polymerase III elongation complex for its stability
with implications to re-initiation". PNAS, 123, 27 e2601775123. https://doi.org/10.1073/pnas.2601775123
3.
Hsin-hung Lin, Yu-Hsiang Lien, I-Ping Tu*,
Wei-Hau Chang* (2026). “Use of a
Coulombic potential framework for interrogating the copper resolvability,
identity and nuclearity in pMMO Cryo-EM maps”. Journal of Chinese Chemical
Society 0, pp 1-11.
4.
Ching-Feng Chen, Szu-Chi Chung, Wei-Hau Chang* and I-Ping Tu* (2025). “EM-2SDR: unsupervised
clustering of 3D conformations directly from 2D cryo-EM images via
tensor-structure modeling”. Annals of Mathematical Sciences and
Applications 10, 427-441.
5.
Claudia Morais
Parada, Ching-Cher Sanders Yan, Cheng-Yu Hung, I-Ping Tu, Chao-Ping Hsu*,
Yu-Ling Shih* (2024). “Growth-dependent
concentration gradient of the oscillating Min system in Escherichia coli”.
J Cell Biol (2025) 224, e202406107.
6.
Hsin-Hung Lin, Chun-Hsiung Wang, Shih-Hsin Huang, Sam Song-Yao Lin, I-Ping Tu, Naoki Hosogi, Chihong Song, Kazuyoshi Murata, Chi-Huey Wong*, Tsui-Ling
Hsu*, Wei-Hau Chang* (2024). “Use of phase plate
cryo-EM reveals conformation diversity of therapeutic IgG with 50 kDa Fab
fragment resolved below 6 Å”. Scientific Reports 14,
14079.
7.
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 RAD51–ADP double
filament structure unveils the mechanism of filament dynamics in homologous
recombination’’. Nature
Communications 14, 4993.
8.
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.
9.
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
10.
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.
11.
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.
12.
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.
13.
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.
14.
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
15.
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.
16.
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.
17.
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.
18.
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.
19.
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.
20.
I-Ping Tu (2013). “The Maximum
of a Ratchet Scanning Process over a Poisson Random Field”. Statistica Sinica,
23, 1541-1551.
21.
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.
22.
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.
23.
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.
24.
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.
25.
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.
26.
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.
27.
I-Ping Tu*, Hung Chen, Xin Chen (2009). “An Eigenvector Variability
Plot”. Statistica Sinica 19, 1741-1754.
28.
I-Ping Tu (2009). “Asymptotic
Overshoot for Arithmetic IID Random Variables”. Statistica
Sinica 19, 315-323.
Conference Papers
1.
Y. Ku, F. Liu, C. Hsu, M.
Chang, S. Hung, I. Tu, W. Chen* (2025). “Optimizing encrypted neural networks:
Model design, quantization and fine-tuning using FHEW/TFHE”. Proceedings on
Privacy Enhancing Technologies Symposium 2025.
2.
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.
3.
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.
4.
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.
5.
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.
6.
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.
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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.
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Presentations in 2019 |
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Presentations in 2020 |
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Presentations in 2021 |
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Presentations in 2023 |
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Presentations in 2024 |
1.
2024.5.28 “An
Empirical Hierarchical Bayesian Method and Application to Cryo-EM Analysis”,
SiegmundFest24, hosted by The Department of Statistics, Stanford University. (Invited Speaker). https://statistics.stanford.edu/events/siegmundfest24.
2.
2024.9.18 “A Hierarchical Linear Model for Cryo-EM Analysis”, The Department of Statistics, Rutgers
University (Invited
Speaker).
3.
2024.10.5 “Good Statistical Practices (GSP): A must toward a successful
and responsible science career”, 2023 Ethics Course at TIGP, Academia Sinica (Invited Speaker).
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Presentations in 2025 |
1.
2025.8.2 “A statistical method for cryo-electron microscopy data
analysis” Next-Generation Statistics: From Theory to Practice in a Data-Rich
Era, Vanderbilt University, USA. (Invited Speaker).
2. 2025.11.1 “Good Statistical Practices (GSP): A must toward a successful and responsible science career”, 2024 Ethics Course at TIGP, Academia Sinica (Invited Speaker).
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Presentations in 2026 |