Mohit Kumar Jolly

The paper shows that interconnected axes of phenotypic plasticity in breast cancer drive coordinated cellular behavior and influence clinical outcomes through mutual inhibition between two teams of plasticity-related nodes.

The paper introduces a multilevel Boolean model to capture hybrid epithelial-mesenchymal phenotypes, revealing more stable and biologically relevant hybrid states than traditional binary models.

The paper identifies a HOXA10-TWIST2 antagonistic circuit that drives partial epithelial-to-mesenchymal transition in the endometrium, essential for embryo implantation.

This paper develops a deterministic model to study how competition and phenotypic plasticity affect adaptive therapy outcomes in cancer, showing that phenotypic transitions can complicate therapy and that asymmetric competition benefits treatment.

The paper analyzes monotone Boolean network models of gene regulatory networks to identify common steady states and multistability patterns, showing epithelial and mesenchymal states are most common in the EMT network.

The paper identifies mechanisms of NRT1.1 phosphorylation switch in plants, showing how phosphorylation and conformational changes regulate nitrate uptake modes.

The paper shows that multi-team competition in gene regulatory networks leads to less stable outcomes compared to binary competition, explaining why binary decisions are common in biology.

This study evaluates fractal measures for distinguishing malignant from normal breast mammograms and assessing molecular subtype differentiation, finding moderate discriminatory performance.

The paper introduces a framework to analyze gene regulatory networks by identifying mutually inhibiting teams of nodes and shows how network topology predicts dynamic behavior.

This study identifies key cellular programs and pathways driving metastatic organotropism in small cell lung cancer using preclinical models and multiomic profiling.

The paper analyzes methylation and transcriptomic data to show that p53 R273H mutation in colon cancer is linked to partial or full EMT states and metastasis.

The paper uses a multiscale model to show that mesenchymally transitioned tumor niches outcompete parental niches under specific adhesion and ECM conditions.

The paper develops a mathematical model to study how cancer cells balance autophagy and apoptosis to determine anoikis resistance.

This study develops a model to analyze how cellular memory and adaptation cost affect survival in fluctuating environments, finding that increased adaptation cost can improve growth by reducing mismatches between cell state and environment.

The paper identifies the TGFβ-ANGPT2-Tie2 axis in cancer-associated fibroblasts that reprograms oral cancer cells to an embryonic-like state, linked to poor prognosis.

This study uses a multiscale mathematical model to explore how EMT influences ovarian cancer progression in two cell lines, finding that EMT and cell cycle parameters significantly affect tumor dynamics.

This study investigates toggle-n networks to understand the dynamics of differentiation into multiple cell states, showing co-expression of transcription factors and the role of cytokine signaling and regulatory asymmetry.

This study identifies a hyper-phosphorylation state in drug-resistant TNBC cells caused by EGFR-to-Src kinase switching, making them vulnerable to EGFR TKI treatment.

The paper uses fractal geometry and DNA walk analysis to identify distinct geometric features in nucleotide patterns of oncogenes and tumour-suppressor genes, highlighting their potential in cancer research.

This study shows that altering macrophage metabolism can reduce drug tolerance in Mycobacterium tuberculosis by affecting bacterial redox states.

The paper shows that coordinated teams in biological networks lead to low-dimensional phenotypic space, with PC1 capturing most variance.

This study investigates how NEAT1 expression changes with substrate stiffness in glioblastoma cells and shows its role in cancer progression through mechano-sensitivity.

The paper investigates lineage-specific coordination of X-chromosome inactivation and active-X upregulation in female cells across different developmental contexts and identifies UTF1 as a mediator of X-upregulation erasure in some lineages.

The paper develops a minimal model to study how planar cell polarity emerges from local interactions and global gradients, showing that gradients enhance robustness and directionality.

This study compares the expression of oncogenic lncRNAs NEAT1 and MALAT1 in 2D and 3D cancer cultures, showing significant differences and functional impacts in 3D tumoroids.

This study shows drug-resistant ovarian cancer cells exhibit collective amoeboid dynamics that enhance their ability to colonize and invade tissues.

This study maps the SCLC tumor microenvironment and identifies cancer-associated fibroblasts as key drivers of neuroendocrine state plasticity and poor prognosis.

The paper analyzes phenotypic heterogeneity in glioblastoma by examining subtype antagonism in transcriptomic data, finding that the proneural-mesenchymal axis is the dominant antagonistic pair.

The paper studies a four-node mutually repressive network, showing it allows for six stable double-positive states and applies this to explain Th1/Th2/Th17/Treg differentiation.

The paper identifies mutually exclusive gene regulation patterns between noradrenergic and mesenchymal states in neuroblastoma, linking them to phenotypic plasticity and therapy resistance.