Nabin Giri

Nabin Giri

PhD candidate in computer science at the University of Missouri, Columbia. Interested in machine learning, computer vision, natural language processing, and bioinformatics

Hi there! 👋

I am a PhD candidate in Computer Science with a minor in Statistics at the University of Missouri, specializing in deep learning and bioinformatics. As a graduate researcher in the Bioinformatics and Machine Learning Lab, I develop innovative solutions at the intersection of statistics, deep learning, and structural biology.

Feel free to reach out if you’d like to discuss any of these topics or simply connect—I am always open to engaging conversations and collaborations!

Recent Achievements

  • Jul 20, 2024   Published a blog post on Nature Portfolio Communities: Read here.
  • Jul 01, 2024   Our paper, De novo atomic protein structure modeling for cryoEM density maps using 3D transformer and HMM, is now available in Nature Communication. Paper . Cryo2Struct Code
  • Jun 19, 2024   Our paper, Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge , is now available in Nature Methods. Paper .
  • May 08, 2024   Our paper, Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures , is now available in Nature Scientific Data. Paper . Cryo2StructData Code
  • Sep 1, 2023   Featured in a blog post by BIOVIA - Journey into Nabin Giri’s BIOVIA Internship: Conformational Sampling with AlphaFold 🌟
  • Jul 13 - 16, 2023   Attended Oxford Machine Learning Summer School (OxML 2023) : Health Track (MLx Health)
  • Jun 30, 2023   Our paper, Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15 , is available in PROTEINS. Paper
  • Feb 9, 2023   Our paper, Deep learning for reconstructing protein structures from cryo-EM density maps: recent advances and future directions , is available in Current Opinion in Structural Biology. Paper
  • Jan 11, 2023   Featured in an article discussing our achievement in CASP15 - Mizzou Engineering News 🌟
  • Jan 6, 2023   Our paper, Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge , is available in Biomolecules Paper
  • Nov 20, 2022   Our method, Template-based Modeling for Accurate Prediction of Ligand-Protein Complex Structures in CASP15 , is available in CASP15 Abstract Book

Misc

I am currently diving into the pages of Don Quixote and The Brothers Karamazov ..📚