Revolutionizing DNA analysis and making it accessible to all through innovative ML-powered analysis and interpretive tools.
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Updated
Aug 25, 2024 - Java
Revolutionizing DNA analysis and making it accessible to all through innovative ML-powered analysis and interpretive tools.
Interactive Protein Sequence VIsualization/Viewer - Interactive Circos
Recurrent neural network implementations for protein secondary structure prediction and language models
A Python package that has functions for featue calculation of protein sequences. Features that are calculated by this package are niched for Epitope prediction.
This Google colab notebook, allows for conservation analysis of user input genes, on their local machine. It relies on the MMSeq2 introduced by https://www.nature.com/articles/s41592-022-01488-1
Sequence generation/sequence to sequence learning using amino acid sequences of Corona virus (SARS-COV2) by training on generative adversial network (GAN)
An unofficial re-implementation of PiFold, a fast inverse-folding algorithm for protein sequence design, in PyTorch.
IsoAligner: dynamic mapping of amino acid positions across protein isoforms
DNA to Protein sequence perl app.
Protein to RNA reverse translation
In Agglomerative we start with all points as individual clusters and then keep on combining clusters until required number of clusters are not formed using linkages like single, complete, average, ward or centroid.
Association Rules for regex patterns in amino acid sequences
Creating plots using FASTA amino-acid files
Narrowly, Find sequences including nucleotide(or amino acid) spacers (Broadly, you can find the speific sequences of front and back while ignoring the middle sequences), and Write the result of finding them to csv files.(Language: Python3.9)
Python Scripts for Haim Lab (Microbiology Research) Projects
An application for illustrating the relative distances between protein structures.
We're encoding the amino acid sequence into binary strings and building a quantum circuit for each one. Then, we're creating a list of Pauli operators for each circuit, one for each qubit, and multiplying them together to get a badass Hamiltonian.
Homework 2 for MCS 5603 Intro to Bioinformatics. Written in Python.
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