Sheraz Ahmed

Segment Anything for Microscopy

micro_sam finetunes Segment Anything into a light microscopy generalist and a cell/neurite-focused electron microscopy model, plus napari tools for interactive 2d, volumetric and tracking annotation.

iLEC-DNA: Identifying Long Extra-chromosomalCircular DNA by Fusing Sequence-derived Featuresof Physicochemical Properties and NucleotideDistribution Patterns

The paper introduces a computational predictor, iLEC-DNA, for identifying leccDNA using sequence-derived features, outperforming existing methods across multiple species.

Generative adversarial networks in cell microscopy for image augmentation. A systematic review

This systematic review analyzes the use of generative adversarial networks for image augmentation in cell microscopy, highlighting common practices, datasets, and challenges in performance metrics.

NTpred: A robust and precise machine learningframework for in-silico identification of Tyrosine nitration sites in protein sequences

NTpred improves the identification of tyrosine nitration sites in protein sequences using advanced feature extraction and ensemble classifiers, achieving better performance than existing methods on benchmark datasets.

Deep Learning Architectures For the Prediction of YY1-Mediated Chromatin Loops

This paper introduces two deep learning predictors for YY1-mediated chromatin loop prediction, showing improved performance across cell lines and benchmark datasets.

A convNet based multi-label microRNA subcellular location predictor, by incorporating k-mer positional encoding

The paper introduces a kmerRP2vec feature representation method combined with CNN and RNN to predict miRNA subcellular locations, outperforming existing methods on a public dataset.