📄Deep learning applications in single-cell genomics and transcriptomics data analysis

📘Journal: Biomedicine & Pharmacotherapy (I.F.=6.9)
🗓Publish year: 2023

🧑‍💻Authors: Nafiseh Erfanian, A. Ali Heydari, Adib Miraki Feriz,...
🏢University: Birjand University of Medical Sciences, Iran - University of California, Merced, USA - University of Calgary, Calgary, Canada, ...

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#review #deep_learning #single_cell #genomics #transcriptomics

✨Genomic Next-Token Predictors are In-Context Learners

📝 Summary:
In-context learning ICL emerges organically in genomic sequences through large-scale predictive training, mirroring its behavior in language models. This first evidence suggests ICL is a general phenomenon of large-scale modeling, not exclusive to human language.

🔹 Publication Date: Published on Nov 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.12797
• PDF: https://arxiv.org/pdf/2511.12797

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✓ https://xn--r1a.website/DataScienceT

#Genomics #InContextLearning #AI #MachineLearning #LLMs

✨MergeDNA: Context-aware Genome Modeling with Dynamic Tokenization through Token Merging

📝 Summary:
MergeDNA models genomic sequences with a hierarchical architecture and dynamic Token Merging to adaptively chunk bases. This addresses varying information density and lack of a fixed vocabulary, achieving superior performance on DNA benchmarks and multi-omics tasks.

🔹 Publication Date: Published on Nov 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14806
• PDF: https://arxiv.org/pdf/2511.14806

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For more data science resources:
✓ https://xn--r1a.website/DataScienceT

#Genomics #Bioinformatics #MachineLearning #DNA #MultiOmics