arXiv subjects

Sangeeta Bhatia

Publications and source records attributed to Sangeeta Bhatia.

5 recordsLinked to original sources

arXiv2026

Evaluating AI-based Scientific Knowledge Synthesis with Epidemiological Systematic Reviews

Systematic literature reviews (SLRs) are a demanding and high-stakes form of scientific knowledge synthesis that remains underspecified as an evaluation setting for large language models (LLMs). We introduce AgentSLR, a large-scale evaluation harness comprising an SLR automation workflow and an expert annotated dataset covering 16,248 articles, designed to test LLM capabilities across the stages of SLRs in epidemiology. Reference annotations were derived from peer-reviewed studies on WHO priority pathogens and produced by domain experts. The harness evaluates each review stage as a separate unit with dedicated metrics enabling targeted failure analysis. We evaluated five frontier reasoning models and found that no single model dominated across all tasks, showing sub-task specialisation often hidden by aggregate benchmarks. Structured data extraction is a major bottleneck, with no model exceeding an average field-level F1 of 0.67. Estimated costs vary substantially, by up to 96 times across evaluated models. Documented failure modes suggest that the evaluated models are not yet reliable enough for unsupervised deployment in epidemiology, where findings can inform public policy.

cs.IR↗

arXiv2025

Towards Breath Based Diagnostics via Water-mediated Capture of Synthetic Breath Biomarkers in SERS-active Plasmonic Nanogaps

Volatile organic compounds (VOCs) are valuable health indicators, with synthetic breath biomarkers offering rapid and disease specific diagnostics. However, their <100 ppb level exhalation requires mass spectrometry, limiting clinical integration. Surface-enhanced Raman spectroscopy (SERS) offers a portable, cost-effective alternative. Yet, detecting synthetic breath biomarkers, with inherently low Raman cross-sections, at <100 ppb remains challenging. We demonstrate SERS detection down to clinically relevant 10 ppb via water-mediated trapping in hydroxylated nanoporous silica-coated plasmonic nanogaps, using pentafluoropropylamine (PFP) as a representative synthetic breath biomarker. Uniform nanogaps, with >1000 times electric field enhancement, were generated between a gold film and gold-silica core-shell nanoparticle assemblies using electric field-driven evaporation. Oxygen plasma treatment hydroxylated the silica, enabling water-mediated hydrogen bonding that strengthened PFP adsorption, confirmed by density functional theory. This mechanism improved SERS sensitivity by 10000 fold, enabling ppb level PFP detection in mouse bronchial fluid and establishing a VOC capturing SERS platform for breath-based diagnostics.

physics.app-ph↗

arXiv2020

A path-deformation framework for determining weighted genome rearrangement distance

Measuring the distance between two bacterial genomes under the inversion process is usually done by assuming all inversions to occur with equal probability. Recently, an approach to calculating inversion distance using group theory was introduced, and is effective for the model in which only very short inversions occur. In this paper, we show how to use the group-theoretic framework to establish minimal distance for any weighting on the set of inversions, generalizing previous approaches. To do this we use the theory of rewriting systems for groups, and exploit the Knuth--Bendix algorithm, the first time this theory has been introduced into genome rearrangement problems. The central idea of the approach is to use existing group theoretic methods to find an initial path between two genomes in genome space (for instance using only short inversions), and then to deform this path to optimality using a confluent system of rewriting rules generated by the Knuth--Bendix algorithm.

math.CO↗

arXiv2016

Position and content paradigms in genome rearrangements: the wild and crazy world of permutations in genomics

Modellers of large scale genome rearrangement events, in which segments of DNA are inverted, moved, swapped, or even inserted or deleted, have found a natural syntax in the language of permutations. Despite this, there has been a wide range of modelling choices, assumptions and interpretations that make navigating the literature a significant challenge. Indeed, even authors of papers that use permutations to model genome rearrangement can struggle to interpret each others' work, because of subtle differences in basic assumptions that are often deeply ingrained (and consequently sometimes not even mentioned). In this paper, we describe the different ways in which permutations have been used to model genomes and genome rearrangement events, presenting some features and limitations of each approach, and show how the various models are related. This paper will help researchers navigate the landscape of genome rearrangement models, and make it easier for authors to present clear and consistent models.

q-bio.OT↗

arXiv2014

Algebraic double cut and join -- A group-theoretic approach to the operator on multichromosomal genomes

Establishing a distance between genomes is a significant problem in computational genomics, because its solution can be used to establish evolutionary relationships including phylogeny. The "double cut and join" (DCJ) model of chromosomal rearrangement proposed by Yancopoulos et al. has received attention as it can model inversions, translocations, fusion and fission on a multichromosomal genome that may contain both linear and circular chromosomes. In this paper, we realize the DCJ operator as a group action on the space of multichromosomal genomes. We study this group action, deriving some properties of the group and finding group-theoretic analogues for the key results in the DCJ theory.

math.GR↗