Update _pages/about.md

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 🧬 My research interest intersects **"graphs"** with genomics and transcriptomics:
 
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+- In **deep learning in genomics**, my work focuses on utilizing sequence models to decode patterns in DNA sequences, aiming to uncover insights into the transcriptional regulatory networks that integrate cis-regulatory DNA sequences with the activity of trans-regulators. I am developing a yeast large language model (LLM) to better understand the mechanisms of yeast gene expression regulation.
+- In **splice site prediction**, I built a deep dilated residual convolutional neural network to decode the complexities of RNA splicing and understand the impact of genetic variants on cryptic splicing ([Learn more](https://www.biorxiv.org/content/10.1101/2023.07.27.550754v2)).
 - In **genome assembly**, De Bruijn graphs are widely used. For an example of its application, check out my [Han1 assembly](https://doi.org/10.1093/g3journal/jkac321), the first gapless Southern Chinese Han genome.
 - For **pangenome indexing**, I've contributed to making the Wheeler graph recognition problem computationally feasible through innovative heuristic methods combined with an SMT solver ([Learn more](https://doi.org/10.1016/j.isci.2023.107402)).
-- In **genome annotation**, I have utilized graph-based methods to stitch together fragmented DNA and protein alignments, thereby assembling them into more accurate annotations. ([Learn more](https://ccb.jhu.edu/lifton/)).
-- My **transcriptome assembly** work focuses on modeling RNA-Seq data using directed acyclic splice graphs, with ongoing research into graph neural networks to decode the complexities of RNA splicing. ([Learn more](https://www.biorxiv.org/content/10.1101/2023.07.27.550754v2)).
+- In **genome annotation**, I have utilized graph-based methods to stitch together fragmented DNA and protein alignments, thereby assembling them into more accurate annotations. ([Learn more](https://doi.org/10.1101/2024.05.16.593026)).
+<!-- - My **transcriptome assembly** work focuses on modeling RNA-Seq data using directed acyclic splice graphs, with ongoing research into graph neural networks to decode the complexities of RNA splicing. ([Learn more](https://www.biorxiv.org/content/10.1101/2023.07.27.550754v2)). -->
 
-💻 As a staunch advocate for open-source software, I invite you to explore my **[NEWS](https://khchao.com/news/)** page for the latest updates on my projects.
+💻 I am an advocate for open-source software, embracing the philosophy of "build what you need, use what you build". I invite you to explore my **[NEWS](https://khchao.com/news/)** page for the latest updates on my projects.
 
 💬 Feel free to reach out to me for collaborations, discussions, or just to say hi! **[Coffee chat! ☕️](https://calendly.com/kuanhao-chao/30min)**