http://repository.iiitd.edu.in/xmlui/handle/123456789/1263 Fri, 10 Apr 2026 20:02:48 GMT 2026-04-10T20:02:48Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1340 Designing circulating-tumor cells (CTCs) detection method using co-measurement data of single-cell RNA and targeted DNA sequencing R, Omkar Chandra; Kumar, Vibhor (Advisor) Detection of cancer for diagnosis and tracking the prognosis of the patients using liquid biopsy procedure: the extraction of blood for the detection of cells is the least invasive procedure and relatively fast process compared to tissue biopsy, which would make the isolation and analysis of biological samples like exosomes, circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), a preferred approach over solid biopsy via open surgery. Due to the sparsity of the overall count of CTCs in the blood and low genomic content recovery from them, it is hard to identify and characterize CTCs to make insights into the biology of the disease. In this study, we analyzed the concurrent data of single-cell RNA-seq and targeted DNA-seq from 9 pancreatic cancer patients. We developed a pipeline that leverages the nature of concurrent data to identify CTCs from non-CTCs (blood cells). We were able to identify CTCs using the mutation profile and transcriptomic profiles of CTCs. We made fundamental biological insights into pancreatic cancer disease by integrating mutational and transcriptomic profiles of the cells. Thu, 01 Dec 2022 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/1340 2022-12-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1336 Compilation and mining of peptide hormones and their receptors Kaur, Dashleen; Raghava, Gajendra Pal Singh (Advisor) Hormones play a crucial role in communicating information between cells and organs; responsible for regulating almost all the physiological processes of organisms. Thus, it is important to collect, compile and mine hormones associated information. Firstly, a repository Hmrbase2 have been developed to maintain comprehensive information on hormones and their receptors, which is an update of Hmrbase. The information was compiled from literature and public repositories like HMDB, Uniprot, HORDB, ENDONET and PubChem. It contains a total of 12,056 entries, including 7,406 entries for peptide hormones, 753 entries for non-peptide hormones, and 3,897 entries for hormone receptors. The database also includes 5,662 hormone receptor pairs. The database is available free for scientific community (https://webs.iiitd.edu.in/raghava/hmrbase2/. Secondly, systematic attempt has been made to develop a method for predicting peptide hormones using data mining techniques. All models in this study were trained, test and evaluated on a dataset of 1174 hormonal and 1174 non-hormonal peptides. A wide range of machine and deep learning techniques have been implemented to discriminate hormones and non-hormones with high precision. Best performing model based on logistic regression achieved maximum performance AUC of 0.93. Finally, a hybrid method has been developed that combine logistic regression model (alignment free method) with BLAST/motif (alignment-based method) and achieved AUC of 0.96 with MCC of 0.8 on independent/validation dataset. To facilitate research community a web server HOPPred have been developed (https://webs.iiitd.edu.in/raghava/hoppred/). Thu, 01 Dec 2022 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/1336 2022-12-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1334 Finding unique patterns in transcriptome and epigenome of cancer cells Mathur, Arpit; Kumar, Vibhor (Advisor) Background: Studying Chromatin Architecture is paramount to an understanding of cells or nuclei in disease and normal state. With recent advances in genomic technologies and computational power, new domains like Topologically associated domains (TAD) have been discovered. Studying TAD in the context of cancer cells gives insights into how chromatin folding relates to the survival of the patient. Exploiting chromatin interactions from the lens of enhancer-gene interactions is of cardinal value since identifying specific chromatin interactions (enhancer-gene pairs) in disease state cells which are etiology pairs for the disease, and using genomic editing technologies to knockdown these pairs, could be a potential precise and accurate model to beat disease cells, especially cancer cells. Our study is divided into two parts; in the first part, we build a method to understand TAD biology and its implication in estimating patient survival. In the second part of our study, we modified a previously proposed method scEChiA to detect enhancer-gene pairs interactions in cancer-specific cells using RNA-seq profiles. We further validates the predicted interactions with 4D genome2 and Activity by Contact (ABC) databases Results: We identified TAD chr1_171750000_172350000 in Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) cancer type, which according to our curated algorithms and pipelines is found to be the most survival TAD with high survival score. We explored this TAD biology of how genes in this TAD interplay with each other creating a network that ultimately defines this TAD property. From the scEChiA R package, we identified several enhancer- 8 enhancer, enhancer-gene, and gene-gene interaction pairs in chromosome 11 of Diffuse large B cell lymphoma (DLBCL) cancer type, which was benchmarked with 4D genome and Activity by contact chromatin interaction databases. Conclusion: Identification of specific TAD, which is most surviving in cancer cell lines, and understanding its underlying biology gives a new definition of TAD property and function. Chromatin interaction results from scEChiA along pipelined developed algorithms give enhancer-gene, enhancer-enhancer, and gene-gene interactions, which could be a database for potential target whose knockdown could be a potential cure to cancer cells. Thu, 01 Dec 2022 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/1334 2022-12-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1333 Studying priming and poising of cells Ansari, Ariba; Kumar, Vibhor (Advisor) An increase in research and development of single-cell genomics led to various insights into cells and their function, it has become a primary focus of research leading to many great discoveries. RNA velocity is one such method obtained through single-cell genomics data that gives information on newly transcribed pre-mRNA and mature mRNA and distinguishes among them. It gives the ratio of spliced and unspliced mRNA, reveals the lineage relationships of a single cell, and predicts its future state on a time scale in a high-dimensional vector. One another great application of single-cell data is pathway enrichment analysis which gives the enriched biological pathways in a gene list. Here we aim to trace the lineage of single cells through RNA velocity and to find the pathways affecting the directionality of priming and poising of cells to get insights into the pathways activities. That is, which pathways are enriched during which lineage of cells will reveal which pathways are helping the cells to differentiate towards a particular lineage. Getting the relationship between the lineage of cells and the enriched pathways will be of great help in fields such as 3D bioprinting of organs and tissues, formation of organoids, and regenerative medicines. Thu, 01 Dec 2022 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/1333 2022-12-01T00:00:00Z