Research
Genome Organization
A topological screen in Drosophila cells lacking CTCF and Cp190 identifies hundreds of insulator elements that modulate local chromatin interactions without driving global genome folding, suggesting Cp190 functions by promoting insulator protein cobinding rather than loop formation [2023, PMID: 36735780]. — Yuri B. Schwartz
Repressed TADs are 3D structural units of chromosome organization in Drosophila [2018, PMID: 295038]. — Giacomo Cavalli
Publications
- Topological screen identifies hundreds of Cp190- and CTCF-dependent Drosophila chromatin insulator elements
2023 · Science Advances - Pattern recognition of topologically associating domains using deep learning
2022 · BMC Bioinformatics - HiCmapTools: a tool to access HiC contact maps
2022 · BMC Bioinformatics
Code Docs - TADs are 3D structural units of higher-order chromosome organization in Drosophila
2018 · Science Advances
Sequence Alignment & Phylogenetics
Sampling alignment columns across alternative aligners enhances the discriminative power of bootstrap support regarding tree topology correctness [2019, PMID:30726875]. — Cedric Notredame
The reliability of Multiple Sequence Alignments (MSA) can be robustly quantified using the Transitive Consistency Score (TCS), which is derived from the T-Coffee pairwise library. — Cedric Notredame
- method [2014, PMID: 24694831]
- server [2015, PMID: 25855806]
Data & Code
- BigBigTree Web server
Tree reconstruction for large orthologous families.
Publications
- Incorporating alignment uncertainty into Felsenstein’s phylogenetic bootstrap to improve its reliability
2021 · Bioinformatics
Code Docs - PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases
2016 · Nucleic Acids Research
Web server - Multiple sequence alignment modeling: methods and applications
2016 · Briefings in bioinformatics - TCS: a web server for multiple sequence alignment evaluation and phylogenetic reconstruction.
2015
Web server - Alignathon: A competitive assessment of whole-genome alignment methods
2014 - TCS: A new multiple sequence alignment reliability measure to estimate alignment accuracy and improve phylogenetic tree reconstruction
2014 · Molecular Biology and Evolution - Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee
2012 · BMC Bioinformatics - Using the T-Coffee package to build multiple sequence alignments of protein, RNA, DNA sequences and 3D structures
2011 · Nature Protocols - T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension
2011 · Nucleic Acids Research - Improving the Alignment Quality of Consistency Based Aligners with an Evaluation Function Using Synonymous Protein Words
2011 · PLoS One - Constrained multiple sequence alignment tool development and its application to RNase family alignment.
2002 · Proc IEEE Comput Soc Bioinform Conf
Single-Cell Data Analysis
scGHSOM adapts the Growing Hierarchical Self-Organizing Map (GHSOM) for single-cell data to enable hierarchical clustering and visualization while identifying significant attributes that characterize cell subpopulations [2025, PMID: 40811172]. — Fang Yu
Publications
- scGHSOM: A Hierarchical Framework for Single-Cell Data Clustering and Visualization
2026 · IEEE Transactions on Computational Biology and Bioinformatics
Code - How Stable Are Single-Cell Embeddings? A Comprehensive Analysis of Dimensionality Reduction Under Input Shuffling
2026 · BIO Web of Conferences - Single-cell absolute contact probability detection reveals chromosomes are organized by multiple low-frequency yet specific interactions.
2017 · Nature communications
Computational Protein Function Prediction
Position-Specific Scoring Matrices (PSSMs) contain richer information than primary sequences and can be efficiently generated by searching the UniRef50 database with reduced sensitivity parameters [PMID:24146760].
Dimensionality reduction techniques, such as PLSA, CA, and PCA, not only enhance model performance but also uncover latent relationships within the data [PMID:18260102, PMID:24146760].
Data & Code
- PSLDoc Code
Subcellular localization from gapped dipeptides and probabilistic latent semantic analysis.
Publications
- GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms
2020 · BMC Bioinformatics
Code - MS2CNN: predicting MS/MS spectrum based on protein sequence using deep convolutional neural networks
2019 · BMC Genomics
Code - The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
2019 · Genome Biology - PSLCNN: Protein Subcellular Localization Prediction for Eukaryotes and Prokaryotes Using Deep Learning
2019 · 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI)
Code - Efficient and Interpretable Prediction of Protein Functional Classes by Correspondence Analysis and Compact Set Relations
2013 · PLoS One - Prediction of nuclear proteins using nuclear translocation signals proposed by probabilistic latent semantic indexing.
2012 - PSLDoc: Protein subcellular localization prediction based on gapped-dipeptides and probabilistic latent semantic analysis
2008 · Proteins: Structure, Function and Genetics
Cancer Genomics
Circulating exosomal miRNAs are candidate liquid-biopsy markers for epithelial ovarian cancer. Working with Ramathibodi Hospital, Bangkok, we analysed paired normal and tumour tissue from 45 patients to select miRNAs that separate ovarian cancer subtypes, and reviewed the diagnostic evidence for circulating exosomal miRNAs in the disease [2021, 10.3390/biomedicines9101433]. — Natini Jinawath, Meng-Shin Shiao
Publications
- Circulating Exosomal miRNAs as Biomarkers in Epithelial Ovarian Cancer
2021 · Biomedicines - Identification of Alternative Splicing Characteristic Associated with Clear-Cell Ovarian Cancer from Paired Normal and Tumor Tissues
2019 · 2019 International Conference on Machine Learning and Cybernetics (ICMLC)