Biology subjects

Das, A. B.

Publications and source records attributed to Das, A. B..

3 recordsLinked to original sources

bioRxiv2026

A lightweight codon-based DNA Transformer for Regulatory Region Identification in the Genome

We developed a lightweight codon-based DNA Transformer equipped with multi-head self-attention and an adaptive classifier head, which achieves exon intron classification with high accuracy and also has moderate accuracy in CDS classification and splice site recognition. We named this model as ExIT (Exon-Intron Transformer). We have implemented codon tokenization for this model. This has been validated on the human genome with external validation from the chimpanzee genome. Further benchmarking has implied that our model is better than the existing models in the above tasks.

bioinformatics↗

bioRxiv2020

Lung Disease Network Reveals the Impact of Comorbidity on SARS-CoV-2 infection

Higher mortality of COVID19 patients with comorbidity is the formidable challenge faced by the health care system. In response to the present crisis, understanding the molecular basis of comorbidity is essential to accelerate the development of potential drugs. To address this, we have measured the genetic association between COVID19 and various lung disorders and observed a remarkable resemblance. 141 lung disorders directly or indirectly linked to COVID19 result in a high-density disease-disease association network that shows a small-world property. The clustering of many lung diseases with COVID19 demonstrates a greater complexity and severity of SARS-CoV-2 infection. Furthermore, our results show that the functional protein-protein interaction modules involved RNA and protein metabolism, substantially hijacked by SARS-CoV-2, are connected to several lung disorders. Therefore we recommend targeting the components of these modules to inhibit the viral growth and improve the clinical conditions in comorbidity.

systems biology↗

bioRxiv2019

Registration for Image-Based Transcriptomics: Parametric Signal Features and Multivariate Information Measures

Image-based transcriptomics involves determining spatial patterns in gene expression across cells and tissues. Image registration is a necessary component of data analysis pipelines that study gene expression levels across different cells and intracellular structures. We consider images from multiplexed single molecule fluorescent in situ hybridization (smFISH) and multiplexed in situ sequencing (ISS) datasets from the Human Cell Atlas project and demonstrate a novel approach to groupwise image registration using a parametric representation of images based on finite rate of innovation sampling, together with practical optimization of empirical multivariate information measures.

bioinformatics↗