Martin Smith
@martinalexsmith
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Genomics technocrat, Bioinformatics, RNA & Bash-Fu 🥷; Director @ramacgenomics ; Associate Prof. @UNSWBABS ; Member of @UNSWRNA
Sydney, New South Wales
Joined April 2012
RT @anglixue: New preprint alert: Excited to share our analysis on the impact of genetic variants on single-cell c….
medrxiv.org
Understanding how genetic variation influences gene regulation at the single-cell level is crucial for elucidating the mechanisms underlying complex diseases. However, limited large-scale single-cell...
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Early bird deadline extended for #AGTA #AGTA2025.This year will be quite different to previous AGTAs, with a big focus on tech, low cost Rego, and in a central location. The venue will have exhibitor lounges (à la AGBT) and two lightning talk sessions, open to industry members.
🚨 BREAKING: Early Bird Extended to 20th Sept. AGTA2025 is the genomics event of the year .Register: @Roche @OlinkProteomics @ramacgenomics @AGRF_genomics @Tecan_Talk @thermofisher @Decode_Science @oxfordnanopore @RevvityInc @mettlertoledo @GarvanInstitute
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"You are not a banana" 🍌.We mapped the human genome decades ago, but most of it is still a black box. Now, UNSW scientists have developed a tool to peer inside–which could reshape how we think about disease.
unsw.edu.au
We mapped the human genome decades ago, but most of it is still a black box. Now, UNSW scientists have developed a tool to peer inside and what they find could reshape how we think about disease.
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RT @martinalexsmith: (8/8) This work provides a rigorous way to benchmark predictors, sharpen them with ML, and apply them to genomic data….
academic.oup.com
Abstract. Accurate prediction of RNA secondary structures is essential for understanding the evolutionary conservation and functional roles of long noncodi
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This work was led by @non_coding_gal with contributions from @sauvagem1 and Prof John Mattick. Research conducted at @CR_CHUSJ @med_umontreal @ircm_mtl @UNSWScience @UNSWRNA with support from @FRQS1 @NSERC_CRSNG @Alliance_Can.
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(8/8) This work provides a rigorous way to benchmark predictors, sharpen them with ML, and apply them to genomic data – a step toward more reliable lncRNA annotation and understanding the hidden roles of RNA structure in #biology. 📄 Read the paper 👉
academic.oup.com
Abstract. Accurate prediction of RNA secondary structures is essential for understanding the evolutionary conservation and functional roles of long noncodi
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(7/8) We tested ECSFinder on one of the few lncRNAs with experimentally validated structure: hTERC, the RNA template of telomerase. The framework correctly recovered its conserved structural features — showing the power of combining benchmarking + ML-selected signals.
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(6/8) We then used #MachineLearning to identify which covariation and conservation features truly help. By integrating the best-performing ones into ML models, we improved their ability to predict conserved RNA structures, as implemented in a new #bioinformatics tool: ECSfinder.
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(5/8) The challenge? Covariation is subtle, noisy, and measured in many ways. Methods disagree, and benchmarking, inconsistent. We built a framework that simulates the experimental conditions under which conserved RNA structures are predicted, allowing fair comparisons.
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(4/8) This is especially important for lncRNAs. The number of known #lncRNA genes has exploded with long read sequencing—now outpacing protein-coding genes. Yet their functions remain poorly understood. Identifying their conserved structures is one way to unlock their biology
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(3/8) At the 2D level — the helices and loops formed by base-pairing — prediction is much more tractable. Here, base pair covariation across species is the key signal: when two nucleotides evolve together to preserve structure, like in this mitochondrial tRNA for glutamine
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(2/8) Predicting 3D #RNAstructure remains very hard, even with AI. Recent benchmarks show deep-learning tools still struggle on novel RNAs (c.f. Bahai et al, 2024, PLoS Comp Bio).And while AlphaFold 3 can model RNA, its accuracy lags far behind proteins:
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RNA is far more than a messenger. Its structures regulate, evolve, and catalyze — carrying out functions DNA and proteins cannot alone. But predicting #RNA structure from sequence is still extremely difficult. In our latest NAR paper, we present a way forward. 🧵 ⤵️
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20k cells + sequencing for AU$660.
[Ramaciotti Centre for Genomics- Parse SPLiT-seq single-cell RNA sequencing promotion] -
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🥱 Bored during #ScienceWeek2025? .🥼 Want to go on an adventure from the comfort of your pyjamas? .🧪🧬Why not go on an immersive & interactive virtual tour of a #Genomics #Lab? .Wander around the @ramacgenomics Centre with impunity here ➡️ #UNSWscience
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RT @strnr: The evolution of high-order genome architecture revealed from 1,000 species 🧬🖥️🧪 .
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🧐 Check out the new and improved Ramaciotti Centre for Genomics, UNSW website 💫 Now with more clarity, less complexity 🔗
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RT @GenomeBrowser: We turn 25 today!. July 7th marks the 25th anniversary of the human genome going online and the start of the UCSC Genome….
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🌅🐦⬛Early bird Registration for #AGTA2025 is live! .Submit your abstract 📝 and check-out the awesome 🗓️ program here ➡️
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