Aanchal Mongia

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics data, showing improved performance over existing methods in diabetic tissue analysis.

Computational prediction of Drug-Disease association based on Graph-regularized one bit Matrix completion

This paper predicts drug-disease associations using a graph-regularized one-bit matrix completion framework, showing superior performance over existing methods.

Predicting heterogeneity in clone-specific therapeutic vulnerabilities using single-cell transcriptomic signatures

The paper uses single-cell RNA-seq data to predict drug responses and combinations by analyzing intra-tumor transcriptomic heterogeneity in cancer cell lines.

FITs: Forest of imputation trees for recovering true signals in single-cell open chromatin profiles

FITs recovers true signals from sparse and noisy single-cell open-chromatin profiles by using a forest of imputation trees to avoid bias and preserve cell-type-specific activity.

deepMc: deep Matrix Completion for imputation of single cell RNA-seq data

deepMc uses deep matrix factorization to impute missing values in single cell RNA-seq data, improving clustering, differential expression analysis, and cell type separability.

Drug-Target Interaction prediction using Multi-Graph Regularized Deep Matrix Factorization

This paper introduces a deep learning framework for drug-target interaction prediction that incorporates multiple similarity matrices to improve performance on benchmark datasets.

McImpute: Matrix completion based imputation for single cell RNA-seq data

McImpute improves single cell RNA-seq data by imputing dropouts, enhancing clustering, differential expression, and visualization.

Drug-Target Interaction prediction using Multi Graph Regularized Nuclear Norm Minimization

This paper introduces a method to predict drug-target interactions using multi graph regularized nuclear norm minimization, showing improved performance over existing methods.