Tag: Bioinformatics
-
Extended abstract of our IEEE DSAA24 paper is now available
The extended abstract of our paper, “p-ClustVal: A Novel p-adic Approach for Enhanced Clustering of High-Dimensional scRNASeq Data” is available at IEEE Xplore (https://ieeexplore.ieee.org/document/10722799)
-
Enhancing Cluster Discernment in High Dimensional Single Cell RNA Sequencing Data
Excited to share that our recent work on using alternate data representation for enhancing cluster discernment in high dimensional single cell RNA Sequencing data has been accepted at the 11th IEEE International Conference on Data Science & Analytics (DSAA 2024).
-
An Extended de Bruijn Graph for Feature Engineering Over Biological Sequential Data
Mert Onur Cakiroglu, Hasan Kurban, Parichit Sharma, M Oguzhan Kulekci, Elham Khorasani Buxton, Maryam Raeeszadeh-Sarmazdeh, Mehmet M Dalkilic – Machine Learning: Science and Technology
-
De Bruijn Graphs
Introduction De Bruijn graphs, named after Dutch mathematician Nicolaas Govert de Bruijn, are invaluable in both computer science and bioinformatics. These graphs efficiently represent overlaps between sequences of symbols, making them essential for sequence analysis applications. While their utility spans various fields, they are predominantly applied in bioinformatics today. We have even recently demonstrated that
Kurban Intelligence Lab 