Implementation of Protein Classification based on subcellular localization using ProtBert(Rostlab/prot_bert_bfd_localization) model from Hugging Face library, based on BERT model trained on large corpus of protein sequences.

A model for predicting short antimicrobial peptides (length <=30 residues) using multiple features and deep learning approaches

Here is the application of Computer vision- Blob Detection methodology to detect and count the Envelope protiens of sample images of Human Coronavirus and mouse hepatitis virus (Image source- https://www.utmb.edu/virusimages/VI/coronaviruses and cdc)

Provided with given sequence of protiens, I create a model to predict whether a given proten is Interacting or Not-Interacting

The transition from primary to secondary protein structure involves the folding of linear amino acid sequences (primary structure) into regular patterns like alpha-helices and beta-sheets (secondary structure). Deep learning-based prediction algorithms leverage neural network architectures to infer these patterns from primary sequence data.