Shamim Ara Mollah

Deciphering epigenetic influence of curcumin on histone signatures in breast cancer using 3D network

This study uses a 3D network model to identify curcumin-induced histone codes and phosphoproteins in breast cancer, linking them to neuropathy-related genes.

gen3DNet: An R Package for Generating 3D Network Models

The paper introduces an R package, gen3DNet, for generating 3D network models from two correlated data objects with shared factors, using non-negative matrix factorization and partial least squares regression.

Identification Drug Targets for Oxaliplatin-Induced Cardiotoxicity without affecting cancer treatment through Inter Variability Cross-Correlation Analysis (IVCCA)

The paper introduces IVCCA, a bioinformatics tool to identify drug targets for oxaliplatin-induced cardiotoxicity without affecting cancer treatment, finding new pathways like energy metabolism as potential therapeutic targets.

The chromatin landscape of healthy and injured cell types in the human kidney

The paper defines the chromatin landscape of healthy and injured kidney cells using multi-omics data, identifying regulatory elements and transcription factor networks involved in injury response.

CREWdb 1.0: Optimizing Chromatin Readers, Erasers, and Writers Database using Machine Learning-Based Approach

CREWdb 1.0 uses machine learning to predict and classify chromatin regulator proteins, improving the accuracy of a database for readers, erasers, and writers.

NeTOIF: A Network-based Approach for Time-Series Omics Data Imputation and Forecasting

NeTOIF improves time-series omics data imputation and forecasting by integrating network-based methods and LSTM networks, outperforming existing techniques in handling missing values across multiple time points.

Increasing metadata coverage of SRA BioSample entries using deep learning based Named Entity Recognition

The paper uses deep learning for Named Entity Recognition to predict missing metadata in SRA BioSample entries, achieving high accuracy for species, condition, and strain categories.