Jiangning (John) Song
@supercs08
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Director of Data-driven Bioinformatics and Biomedicine Lab | Professor of Monash University | Assoc Editor of IEEE J Biomed Health Infomatics, BMC Bioinform
Melbourne, Victoria
Joined August 2017
We have 2 open RA+PhD positions in our AI-driven Bioinformatics & Biomed Lab @MonashBDI, for onshore students with strong CS, SE/ EE background & interest in medical imaging, starting any time soon, supported by Monash Major & Seed IDR Grants. Welcome to contact me if interested.
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RT @naturemethods: Two absolutely fantastic bioimage analysis papers out today offering exceptional, generalizable tools for segmentation--…
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RT @tbepler1: Excited to share PoET-2, our next breakthrough in protein language modeling. It represents a fundamental shift in how AI lear…
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RT @BiologyAIDaily: Self-iterative multiple instance learning enables the prediction of CD4+ T cell immunogenic epitopes 1. ImmuScope is a…
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RT @ItaiYanai: How to write a grant? 1. Write it for the reviewer, not you, the applicant. 2. Communicate in stories. 3. Make your story co…
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- DrugDAGT accurately predicts synergistic drug combinations for SARS-CoV-2 treatment. - We expect DrugDAGT to accelerate the discovery of safe and effective drug combinations for complex therapeutic applications. @YaojiaChen0807
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- We expect DrugDAGT to accelerate the discovery of safe and effective drug combinations for complex therapeutic applications. Paper: Code:
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- DrugDAGT effectively identifies key local structures critical to DDI outcomes, as evidenced in interactions involving ketoconazole and loxoprofen with various drugs. - DrugDAGT accurately predicts synergistic drug combinations for SARS-CoV-2 treatment.
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- DrugDAGT demonstrates significant improvements in DDI prediction for both warm-start and cold-start scenarios, leveraging the combined strengths of the graph transformer and contrastive learning frameworks.
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- Fine-tuning EPACT on 3D data identifies binding hotspots within the TCR-pMHC complex and corroborates the presence of T cell cross-reactivity. - EPACT is anticipated to accelerate the development of TCR-based immunotherapies and vaccines for infectious diseases and cancers.
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RT @YumingGuo007: Our global analyses find despite a decline in absolute PM2.5 concentrations, suburban and urban areas in very-high-HDI re…
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RT @LeoTZ03: Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and struc…
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RT @ItaiYanai: It’s a lonely job, leading a research group (professor, principal investigator, group leader – whatever you call it). You ta…
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RT @BiologyAIDaily: Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects @Brief…
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RT @greeninglab: We want @MonashUni to be the place to be for microbiology in the post-metagenomics era. So much going on.
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RT @MonashBDI: 1/Unlocking the secrets of how the third form of life —archaea— makes energy, with potential applications for transitioning…
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RT @MoAlQuraishi: OpenFold paper is now out in @naturemethods. Timely. I’ll say more about AF3 at the end of this thread, but first I wante…
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