Leelavati Narlikar

The paper identifies two groups of transcription factors that show intra-group attraction and inter-group repulsion in both genomic and spatial contexts across human cell lines.

The paper introduces a statistical framework to detect cis-regulatory diversity by modeling regions as combinations of motifs, applied to ChIP-seq and enhancer assays across species.

MINDFUL clusters promoters by TSS alignment into diverse classes without prior knowledge, learning optimal k and avoiding motif discovery limitations.

This study shows Orc4 stabilizes centromeric chromatin by interacting with CENPA and Mcm2, and its spatiotemporal localization is crucial for kinetochore stability in C. albicans.

The paper introduces a method to decompose high-throughput ChIP data into distinct binding components without prior motif knowledge, revealing insights into chromatin complexes and their regulatory roles.

THiCweed detects sequence features in ChIP-seq data by clustering bound regions based on sequence similarity, outperforming existing methods on synthetic and real data.