The Bioinformatics Core Facility was established in early 2007. Our mission is to facilitate the process of integrating bioinformatics know-how and knowledge into biological discoveries. To that end, we provide the following types of services:

1. Consultation: Answering short questions on using bioinformatics software and statistics methods.
2. Computation: Executing user-specified software for specific biological research problems.
3. Research & Development: Customization of necessary bioinformatics tools, and organization of bioinformatics tools for stable operating procedures.
4. IPMB HPC: We help maintaining the high-performance computing (HPC) system owned by IPMB. Please refer the wiki page (intranet link) for more information.
5. Training: We organize bioinformatics workshops and training courses for IPMB members. Please refer our file repository (intranet link) for workshop slides.

Office hour
We will be at room R106 of the IPMB building for every Friday 1:30PM~2:30PM. This office hour will be suspended if other official events are scheduled. We also welcome people to contact us directly for discussions of bioinformatics related questions. For example, data processing using Excel, simple statistics analysis, suggestions on using public databases, or for a second opinion on bioinformatics analysis.

Task initiation
No specific forms are required to fill for initiating a service task. Initial conversation would be required for formalizing requests and turning them into computationally doable form. Please write us an email for making an appointment. It is appreciated if the context of the request could be addressed first.

Charges
The service charge is 1100NTD/working hour. Here are two examples of working hours for Arabidopsis thaliana according to our recent records:

1. RNAseq task: 40M read-sample x 15 will take about 3 working days. The output includes differentially expressed gene discovery and alternative-splicing comparisons.
2. DNAseq task: 50M read-sample x 9 will take about 2.5 working days for SNP/InDel calling and annotation.

Service experiences
Service categories that we have experienced. Our services are including but not limited to the following aspects:

• DNAseq data: Sequence assembly / SNP/InDel detection / T-DNA insertion site detection / Tandem duplication detection / Genome rearrangement detection

SNP-caused premature codon. Data from Dr. Wan-Hsing Cheng’s lab, IPMB

• RNAseq data: Expression level computation / Sample-sensitive alternative splicing events / Alternative polyadenylation detection / Gene fusion detection / scRNAseq data processing

Condition-sensitive intron retention. Detected in 1% data of NCBI SRA SRP071829. Dr. Majori Matzke’s lab, IPMB

• Other NGS analyses: SmallRNA expression level computation / SmallRNA target prediction / ChIPseq data processing

• Systems biology: Co-expression clustering / PPI network computation / Sequence motif searching / GO enrichment computation / Automatic GO annotation

• Miscellaneous: Enzyme kinetics computation / Computation of isothermal tiling array probes / iTRAQ data processing / Protein structure and interaction prediction

Applied public software for interaction prediction

Reference materials
A few presentation files are listed here for your reference:

1. Bioinformatics core introduction, and computing resources in the Academia Sinica campus
2. Using RStudio to write R markdown – a plot making practice
3. Writing R markdown for enrichment analyses
4. Online AlphaFold3 structure prediction and offline structure manipulation
5. DEMOs of protein structure applications

Open source projects
This bioinformatics core facility is also maintaining the following open source projects.

• MACCU (Multi-Array Correlation Computation Utility, https://github.com/wdlingit/maccu/): Computation of co-expression networks and comparisons between networks which help finding tissue-specific co-expression modules.

Gautam et al., Plant Physiol 2021. Dr. Wolfgang Schmidt’s lab, IPMB

• RackJ (Read Analysis & Comparison Kit in Java, http://rackj.sourceforge.net/): In addition to computation of RPKM values of RNAseq data, this toolkit computes read numbers for every exon, intron, and splicing junction, thus enables finding of sample-sensitive alternative-splicing events.

An alternative-splicing event detected by RackJ

• GOBU (Gene Ontology Browsing Utility, https://gobu.sourceforge.io/): A user-friendly graphical interface program for GO data manipulation, including fast computation modules for enrichment analysis.

Selected Publications

Meyer P, Carpentier S, Mithöfer A, Vélez-Bermúdez IC, Lin WD, Herrera HS, Schmidt W, Schmitz-Linneweber C, and Geilfus CM. (2026) Apoplastic pH modulates gene expression, proteome, and ABA content in Vicia faba guard cells, accompanied by reduced stomatal aperture under salt stress. Journal of experimental botany, erag181. Advance online publication. https://doi.org/10.1093/jxb/erag181

Shrestha R, Reyes AV, Carey S, Karunadasa SS, Zhai W, Byun D, Lin WD, Li J, Alerte K, Cui H, Wang ZY, and Xu SL. (2025) Next-Generation Mapping of the ACINUS-Mediated Alternative Splicing Machinery and Its Regulation by O-glycosylation in Arabidopsis. bioRxiv : the preprint server for biology, 2025.01.04.631329. https://doi.org/10.1101/2025.01.04.631329

Vélez-Bermúdez IC, Lin WD, Chou SJ, Chen AP, and Schmidt W. (2025) Transcriptome and translatome comparison of tissues from Arabidopsis thaliana. Scientific data, 12(1), 504. https://doi.org/10.1038/s41597-025-04805-3

Kanno T, Chiou P, Wu MT, Lin WD, Matzke A, and Matzke M. (2023) A GFP splicing reporter in a coilin mutant background reveals links between alternative splicing, siRNAs, and coilin function in Arabidopsis thaliana. G3 (Bethesda, Md.), 13(10), jkad175. https://doi.org/10.1093/g3journal/jkad175

Huang CK, Lin WD, Wu SH (2022) An improved repertoire of splicing variants and their potential roles in Arabidopsis photomorphogenic development. Genome Biol. 9;23(1):50. https://doi.org/10.1186/s13059-022-02620-2

Hsieh EJ, Lin WD, Schmidt W (2022) Genomically Hardwired Regulation of Gene Activity Orchestrates Cellular Iron Homeostasis in Arabidopsis. RNA Biol. 19(1):143-161. https://doi.org/10.1080/15476286.2021.2024024

Kanno T, Venhuizen P, Wen TN, Lin WD, Chiou P, Kalyna M, Matzke AJM, Matzke M (2018) PRP4KA, a Putative Spliceosomal Protein Kinase, Is Important for Alternative Splicing and Development in Arabidopsis thaliana. Genetics. 210(4):1267-1285. https://doi.org/10.1534/genetics.118.301515

Salazar-Henao JE, Lin WD, Schmidt W (2016) Discriminative gene co-expression network analysis uncovers novel modules involved in the formation of phosphate deficiency-induced root hairs in Arabidopsis. Sci Rep 6:26820. https://doi.org/10.1038/srep26820

Kanno T, Lin WD, Fu JL, Wu MT, Yang HW, Lin SS, Matzke AJ, Matzke M (2016) Identification of Coilin Mutants in a Screen for Enhanced Expression of an Alternatively Spliced GFP Reporter Gene in Arabidopsis thaliana. Genetics 203(4):1709-20. https://doi.org/10.1534/genetics.116.190751

Sasaki T, Kanno T, Liang SC, Chen PY, Liao WW, Lin WD, Matzke AJ, Matzke M (2015) An Rtf2 domain-containing protein influences pre-mRNA splicing and is essential for embryonic development in Arabidopsis thaliana. Genetics 200(2):523-35. https://doi.org/10.1534/genetics.115.176438

Chang CY, Lin WD, and Tu SL. (2014) Genome-Wide Analysis of Heat-Sensitive Alternative Splicing in Physcomitrella patens. Plant physiology, 165(2), 826–840. https://doi.org/10.1104/pp.113.230540

Wu HP, Su YS, Chen HC, Chen YR, Wu CC, Lin WD, and Tu SL. (2014) Genome-wide analysis of light-regulated alternative splicing mediated by photoreceptors in Physcomitrella patens. Genome biology, 15(1), R10. https://doi.org/10.1186/gb-2014-15-1-r10

Liu MJ, Wu SH, Wu JF, Lin WD, Wu YC, Tsai TY, Tsai HL, and Wu SH.. (2013) Translational landscape of photomorphogenic Arabidopsis. Plant Cell. 25:3699-710. https://doi.org/10.1105/tpc.113.114769

Lan P, Li WF, Lin WD, Santi S, and Schmidt W. (2013) Mapping gene activity of Arabidopsis root hairs. Genome Biology. 14:R67. https://doi.org/10.1186/gb-2013-14-6-r67

Rodríguez-Celma J, Lin WD, Fu GM, Abadía J, López-Millán AF, and Schmidt W. (2013) Mutually exclusive alterations in secondary metabolism are critical for the uptake of insoluble iron compounds by Arabidopsis and Medicago truncatula. Plant physiology, 162(3), 1473–1485. https://doi.org/10.1104/pp.113.220426

Kesari R, Lasky JR, Villamor JG, Des Marais DL, Chen YJ, Liu TW, Lin W, Juenger TE, and Verslues PE. (2012) Intron-mediated alternative splicing of Arabidopsis P5CS1 and its association with natural variation in proline and climate adaptation. Proceedings of the National Academy of Sciences of the United States of America, 109(23), 9197–9202. https://doi.org/10.1073/pnas.1203433109

Lin WD, Liao YY, Yang TJ, Pan CY, Buckhout TJ, and Schmidt W. (2011) Coexpression-based clustering of Arabidopsis root genes predicts functional modules in early phosphate deficiency signaling. Plant Physiology. 155:1383-402. https://doi.org/10.1104/pp.110.166520