AgBio genomics expert. Exploring new horizons & disruptive innovations in DNA, RNA & Protein sequencing, single cell & spatial omics. 🌱 🥬 🍉 🍏 🫑 🌶 🌽🫐🍌🍓

Wageningen
Joined July 2013
In collaboration with @Roche, Keygene evaluated the Roche AXELIOS 1 platform for samples relevant for AgBio research. The AXELIOS 1 platform has the speed, scale and accuracy to accelerate crop innovation. keygene.com/keygene-eval... #Genomics #NGS #CropInnovation #AXELIOS1
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Pinal is now published in Nature. The 16B-parameter AI model designs functional proteins directly from natural-language prompts. Four protein classes were experimentally validated, including PET-degrading enzymes. A designed H-protein achieved 1.7× the native control’s product yield in a CO₂-fixation system. Paper: nature.com/articles/s41586-0… Code: github.com/westlake-repl/Den…
🧬 Design proteins with natural language. Pinal is now online in Nature! Pinal democratizes computational protein design by turning functional intent into protein candidates. Open weights + code: github.com/westlake-repl/Den… Paper: nature.com/articles/s41586-0…
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Bolero: Predicting cell-state-specific gene regulation from DNA across species biorxiv.org/content/10.64898…
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New OA Article: "Assembly-graph-assisted haplotype-resolved scaffolding of polyploid genomes" rdcu.be/wDfwnP3uLTEa GPhase overcomes key limitations of 3C data and substantially improves the accuracy, completeness and contiguity of complex polyploid genome assembly.
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DeepD is a sparse mixture-of-experts genome model that reads single nucleotides across a 1-million-token context, pretrained on unselected whole genomes from all domains of life. A Context-Anchor-Body strategy let it generate complete yeast chromosomes and megabase-scale Arabidopsis segments preserving gene structure and order. doi.org/10.64898/2026.10.13.…
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Structural variant detection across sequencing technologies nature.com/articles/s41587-0…
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New Huang lab publication at Nature. Our newly developed technique: transient Pore Analyte Looping (tPAL) now achieves “chop and measure” nanopore sequencing of peptide, in an amino acid by amino acid manner. nature.com/articles/s41586-0…
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Have you ever looked at a gene in IGV or a genome browser and wondered “What are all those (ATAC-seq/H3K27ac/CTCF ChIP-seq/…) peaks doing?” 🤔 I’m thrilled to share that we developed a new technology called Swap-seq to answer that exact question. biorxiv.org/content/10.64898…
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#SpliceAI2 technical deep dive: transcript prediction and training. We perfectly reconstructed the top transcript for 82% of held-out genes. How? Splice graphs, dynamic programming, and long-read RNA-seq. 🧬✂️🧵
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New Article: "Maternal epigenetic regulation of embryonic patterning in plants" rdcu.be/1S5Hxp2SHTTa Post-fertilization remodelling of H3K27me3 in integuments regulates the timely activation of auxin transport genes => maternal-to-embryo IAA transport and embryo patterning.
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A paper in Nature introduces Paper2Agent, an automated framework that converts research papers into AI agents that functions as a virtual corresponding author. go.nature.com/4hgRMBH
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Today, Sculpta releases the first demonstration of bioorthogonal barcoding ("bobcoding"), the process by which we: 1) covalently attach oligonucleotide barcodes to RNA at multiple internal positions with two-step chemistry, and 2) perform a multiplexed reverse transcription reaction to generate barcoded cDNA libraries with >99% barcoding accuracy. To the best of our knowledge, it is the first time ever that either of these steps have ever been performed by anyone. No one has ever broken the barrier of multiplexing prior to any enzymatic step in library preparation, driving simplicity and higher data quality. Instead of other methods that add 0 or 1 barcode, we add one barcode every ~300bp, adding redundancy and fidelity to RNA measurements. In our first application described in our pre-print below, we used bobcodes to create the first RNA isoform-resolved drug screening platform. It beats Novartis' DRUG-seq platform by: - generating full length transcript capture of RNA isoforms, instead of just 3' end counting - capturing 25-fold more RNA splicing events - reducing barcode swapping by 10-fold - using 18 fewer PCR cycles (~250,000 less amplification) - reducing sample-to-sample variability in gene expression measurements - eliminating costly and cumbersome library fragmentation/tagmentation steps completely - reducing workflow complexity and number of steps - reducing overall protocol duration by ~25% Though our chemical barcoding method improved transcriptomic data quality while also being simpler and faster than all existing methods, the implications of this work go well beyond this particular use case: The gate to greater applications of AI in transcriptomics is not a lack of compute. Nor is it a lack of data volume. The elephant in the room has always been our limited ability to faithfully and accurately measure cellular RNAs. Sculpta now has line of sight to build what we call the first ground truth transcriptomics platform [for single cell, spatial and more] for the future of biological research, drug development and AI-enabled discoveries for the betterment of human health and longevity. [PS Until the kind folks at bioRxiv get through the apparent backlog of AI slop submissions, Sculpta will host the pre-print PDF on our website. You can sign up for product offerings and other updates at this link too] sculpta.bio/preprint
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Now published in Algorithms for Molecular Biology: link.springer.com/article/10…. Key message: a tiny CNN model with 7k parameters can capture main splice signals across vertebrates+insect and halves the minimap2 & miniprot junction error rate. I always use this new feature now.
Preprint on "Improving spliced alignment by modeling splice sites with deep learning". It describes minisplice for modeling splice signals. Minimap2 and miniprot now optionally use the predicted scores to improve spliced alignment. arxiv.org/abs/2506.12986
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ʙɪɴᴅᴄʀᴀꜰᴛ2 is out, and we're not waiting for the paper. The full code drops today, free for academic and industry use. We're releasing it early so you can start designing right now, and bring its full power to the current Adaptyv competition. github.com/PacesaLab/BindCra…
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npj Genomic Medicine:Long-read transcriptomics - opportunities and challenges. #long-read #nanopore #pacbio #RNA-seq nature.com/articles/s41525-0…
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Spatial Transcriptomics in Plants: From Cellular Maps to Mechanistic Insight cell.com/action/showPdf?pii=… ♻️
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Maybe it’s time to say goodbye to UMAP and other low-dimensional embeddings (at least in many single-cell analyses). We developed MILK to encode single-cell populations into tree representations at unprecedented scales. biorxiv.org/content/10.64898… Here’s what MILK is: 🧵
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