Biology subjects

Sigdel, D.

Publications and source records attributed to Sigdel, D..

5 recordsLinked to original sources

bioRxiv2026

BioPhasor: Decoding Cellular State Tensors from Multi-Omics Phasor Dynamics for Quantum Ready Systems Biology

Integrating multi-omics data--transcriptomics, proteomics, metabolomics, single-cell--remains a fundamental challenge in systems biology. We present BioPhasor, a framework that encodes each measurement as a complex phasor z = ei{phi} on the compact N -torus TN, modelling the cell as phase-coupled oscillatory programs whose dissipative dynamics generate limit cycles and an attractor landscape. From this geometry we derive the Cell State Tensor (CST), a rank-3 tensor whose axes we root in measured multi-omics quantities: a pathway/module atlas on the regulatory axis and a directional central-dogma modality axis. Across nine scenarios on open public data (GEO, CPTAC), loaded through one unmodified data layer, we report verdicts honestly: four reproduce, three are partial, two do not. A data-driven cell-cycle axis lifts agreement with a reference method from 0.34 to 0.69; an explicit circadian origin cuts peak-time error from 10.6 to 1.4 h; and central-dogma coupling--mRNA phase organising protein amplitude--clears a surrogate null and is tumour-specific. Grounding the quantum-ready claim, the CST maps to a density-matrix formalism whose coherence and entropy match quantum-information counterparts, and the phasor circuit transpiles gate-for-gate to a variational quantum circuit, though no empirical advantage emerges. A single loader regenerates every reported number, and the code is released.

bioinformatics↗

bioRxiv2026

Learning the Cellular Dynamics as a Port-Hamiltonian System

We present a physics-inspired classical digital twin of the cell: a graph neural network constrained to a compartmental, multi-clock port-Hamiltonian form, with parameters learned from multi-omic measurements. The port-Hamiltonian structure is a modelling choice -- it buys conservation, passivity and a clean separation of storage, routing and dissipation -- not a claim about what a cell is. The state pairs each species abundance deviation with a phase coordinate, assigned only where a per-clock rhythmicity gate certifies periodicity. Stored energy decomposes over five functional compartments, so stability is verified compartment by compartment. Two distinct clocks are included -- the 24-hour transcription-translation loop and the 20-hour transcription-independent redox oscillator -- coupled through a zero-net-power link, with the central-dogma correspondence hard-wired and moiety pools exact invariants. On a real mouse-liver three-omic dataset the verdict is mixed. Across ten seeds the trained twin is thermodynamically stable (no violations at any sampled state) and forecasts held-out segments (root-mean-square error 0.325 {+/-} 0.002). Its central prediction -- cross-omic phase lag equals arctan of clock frequency over degradation rate -- matches the aggregate transcript-to-protein lag (5.74 {+/-} 0.03 versus 4.90 hours), but the per-gene correlation is indistinguishable from zero (r = 0.06 {+/-} 0.27, sign unstable across seeds), so the law is supported in aggregate and unresolved per species. Recovery of withheld interaction edges is at chance (AUROC 0.50 {+/-} 0.13, nine of ten seeds scoreable): 24 timepoints do not identify network topology, which we report as a bound on what this data volume supports rather than as a property of the framework. Because the port-Hamiltonian form is imposed by construction, edits to the twin preserve it, so specialisation and disease can be expressed as structured perturbations of this reference twin rather than as separate models.

cell biology↗

bioRxiv2025

Molecular dynamics simulations reveal DNA gate opening mechanisms for M. smegmatis topoisomerase 1A

Type 1A topoisomerases relax torsional strain in DNA via a strand passage mechanism in which a protein mediated DNA gate must open during the enzymes catalytic cycle. This gate-open conformational state of the enzyme has been challenging to observe via experimental methods. In this study, we first used equilibrium Molecular Dynamics simulations to probe the structural properties of the gate closed state for the DNA-free apo system and a system with a ssDNA bound at the DNA binding site. For both systems, we followed the equilibrium simulations with Umbrella Sampling simulations. Umbrella sampling allowed us to bias the protein to adopt a gate-open state to study the properties of this conformation, as well as the pathways leading to it. We observed that several electrostatic interactions contribute to the closed-state stability of the protein which were broken during the gate opening. The gate opening comprised of three major domain motions that were determined from simulation trajectories and Principal Component Analysis. Finally, umbrella sampling results combined with the Weighted Histogram Analysis Method allowed us to reconstruct the free energy profiles of gate opening for all simulations. SIGNIFICANCEMulti-drug resistant bacterial strains necessitate newer ways of targeting bacteria. Type 1A topoisomerases are potential anti-bacterial drug targets. Current strategies are to either block the protein binding to DNA or prevent the cut DNA being religated during the catalytic cycle. A possible alternative to these methods would be to trap the protein at an open conformation. Structural information about the transient open state is crucial to this approach. Results of this study provide mechanistic details of gate opening. This information furthers the understanding of the topoisomerase catalytic cycle which will aid in anti-topoisomerase drug design efforts.

biophysics↗

bioRxiv2024

Data-driven insights into the association between oxidative stress and calcium-regulating proteins in cardiovascular disease.

A growing body of biomedical literature suggests a bidirectional regulatory relationship between cardiac calcium (Ca2+)-regulating proteins and reactive oxygen species (ROS), which is integral to the pathogenesis of various cardiac disorders via oxidative stress signaling. To address the challenge of finding hidden connections within the growing volume of biomedical research, we developed a data science pipeline for efficient data extraction, transformation, and loading. Employing the CaseOLAP (Context-Aware Semantic Analytic Processing) algorithm, our pipeline quantifies interactions between 128 human cardiomyocyte Ca2+-regulating proteins and eight cardiovascular disease (CVD) categories. Our machine learning analysis of CaseOLAP scores reveals that the molecular interfaces of Ca2+-regulating proteins uniquely associate with cardiac arrhythmias and diseases of the cardiac conduction system, distinguishing them from other CVDs. Additionally, a knowledge graph analysis identified 59 of the 128 Ca2+-regulating proteins as involved in OS-related cardiac diseases, with cardiomyopathy emerging as the predominant category. By leveraging a link prediction algorithm, our research illuminates interactions between Ca2+-regulating proteins, OS, and CVDs. The insights gained from our study provide a deeper understanding of the molecular interplay between cardiac ROS and Ca2+-regulating proteins in the context of CVDs. Such understanding is essential for the innovation and development of targeted therapeutic strategies.

bioinformatics↗

bioRxiv2024

Mycobacterial Topoisomerase IA Energetically Suffers From C-terminal Deletions

Type IA topoisomerases relieve torsional stress in DNA by a strand-passage mechanism, using the strain in the DNA to drive relaxation. The topoisomerase IAs of the Mycobacterium genus have distinct C-terminal domains which are crucial for successful strand-passage. We used single-molecule magnetic tweezers to observe supercoil relaxation by wild type Mycobacterium smegmatis topoisomerase IA and two C-terminal truncation mutants. We recorded distinct behaviors from each truncation mutant. We calculated the free energy stored in the DNA as it is twisted under force to examine the differences between the proteins. Based on our results, we propose a modified model of the strand-passage cycle.

biophysics↗