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Indraprastha Institute of Information Technology DelhiORCID 0009-0009-6120-2400Unclaimed ORCID profile · follow to get notified of new preprints
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3 papers
Recent·Most cited
P. A. Tijare, Nishant Kumar, Gajendra P. S. Raghava
This paper develops models to predict and design proteins with desired melting temperatures using machine learning and large language models, achieving high accuracy and providing tools for application.
P. A. Tijare, Naman Kumar Mehta, Gajendra P. S. Raghava
This paper benchmarks quantum SVM and classical ML algorithms for predicting therapeutic proteins, finding CML outperforms QSVM but both show promise in peptide prediction tasks.
Anand Singh Rathore, Shubham Choudhury, Akanksha Arora…·Gajendra P. S. Raghava
This paper introduces ToxinPred 3.0, an improved method for predicting peptide toxicity using alignment-free machine/deep learning and ensemble approaches, achieving high accuracy and sensitivity.