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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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19375674 · May 202619922001200920172026
48 results for cell growth

Method improves microbial biomass yield estimation from noisy data.

problem Estimating microbial biomass yields from noisy cell counts and substrate measurements.
method Probabilistic macrochemical modeling to relax cell weight assumptions and improve robustness.
result Model provides accurate uncertainty estimates of key parameters.

We report analytical results for the development of the viscous fingering instability in a cylindrical Hele-Shaw cell of radius a and thickness b. We derive a generalized version of Darcy's law in such cylindrical background, and find it recovers the usual Darcy's law for flow in flat, rectangular cells, with correctio…

2002-01-31abs ↗pdf ↗

The process of morphogenesis, which can be defined as an evolution of the form of an organism, is one of the most intriguing mysteries in the life sciences. It is clear, that gene expression patterns cannot explain the development of the precise geometry of an organism and its parts in space. Here, we suggest a set of …

2012-05-05abs ↗pdf ↗

Essential to each other, growth and exploration are jointly observed in populations, be it alive such as animals and cells or inanimate such as goods and money. But their ability to move, crucial to cope with uncertainty and optimize returns, is tempered by the space/time properties of the environment. We investigate h…

2017-12-04abs ↗pdf ↗

Optimized biopharmaceutical seed train design reduces variability and saves time.

problem Designing robust biotechnological processes with cell cultures.
method Coupling uncertainty-based upstream simulation and Bayes optimization using Gaussian processes.
result Optimized seed train design results in lower cell density variability and reduced process duration.

Cooperation is a persistent behavioral pattern of entities pooling and sharing resources. Its ubiquity in nature poses a conundrum. Whenever two entities cooperate, one must willingly relinquish something of value to the other. Why is this apparent altruism favored in evolution? Classical solutions assume a net fitness…

2015-06-10abs ↗pdf ↗

Forest Fire Clustering discovers cell types from single-cell data.

problem Discovering cell types from large-scale single-cell sequencing data.
method Iterative label propagation and parallelized Monte Carlo simulation.
result Forest Fire Clustering outperforms state-of-the-art methods on diverse benchmarks.

Proposes CCCVAE for better single-cell clustering with cell-cell communication.

problem Improving single-cell RNA sequencing clustering by incorporating cell-cell communication.
method Integrates cell-cell communication into a variational autoencoder framework.
result Empirical results show CCCVAE outperforms standard VAEs in clustering performance.

Matching cells over time has long been the most difficult step in cell tracking. In this paper, we approach this problem by recasting it as a classification problem. We construct a feature set for each cell, and compute a feature difference vector between a cell in the current frame and a cell in a previous frame. Then…

2012-07-13abs ↗pdf ↗

Improved GPLVM model for single-cell RNA-seq data.

problem Lack of effective scalable models for clustering cell types in large-scale single-cell RNA-seq data.
method Introduces amortized stochastic variational Bayesian GPLVM (BGPLVM) tailored for single-cell RNA-seq.
result Matches the performance of scVI on synthetic and real-world datasets and reveals more interpretable latent structures.

The study identifies all possible vector field structures on specific 2D shapes.

problem Optimal discrete gradient vector fields on surfaces with 1-2 critical cells.
method Analysis of discrete vector fields on 2D shapes with minimal critical cells.
result All possible structures of discrete Morse functions on specified shapes.

New model identifies cell-specific genes for cancer prognosis.

problem No statistical model to integrate multiscale cancer data.
method Bayesian generalized promotion time cure models (GPTCMs).
result Improves cancer prognosis by identifying cell-specific genes.

MarkerMap selects key genes for cell type analysis in single-cell RNA-seq.

problem Selecting informative genes from large single-cell RNA-seq datasets is challenging and computationally intensive.
method MarkerMap is a generative model that identifies minimal gene sets explaining cell type variability.
result MarkerMap outperforms existing methods in both supervised and unsupervised marker selection.

New metric scores perturbations across populations, not cells, improving model comparison.

problem Single-cell perturbation data overlaps, making per-cell accuracy unreliable.
method Average per-cell probability vectors over all cells of a perturbation to form a population profile and rank candidate perturbations.
result Classifier Discrimination Score (CDS) identifies true perturbation more reliably than pseudobulk-based scores.

NESS improves neighbor embedding for smooth cell-state transitions in single-cell data.

problem Challenges in extracting smooth, low-dimensional representations from noisy single-cell data.
method Builds on PCS framework to develop NESS, a stable machine learning approach.
result NESS consistently yields useful biological insights across diverse single-cell datasets.

GAGA learns a warped metric for geometry-aware data generation and interpolation.

problem Challenges in generating data with meaningful geometry in high-dimensional datasets.
method Combines manifold learning with generative modeling to learn a warped Riemannian metric.
result GAGA improves trajectory inference by 30% in single-cell population-level data.

New model clusters cells and individuals, revealing genetic influences on cell types.

problem Clustering nested data with group-level and observation-level variables.
method Nested Atoms Model (NAM), Bayesian nonparametric approach.
result Identifies clusters of genetically similar individuals with homogeneous cell-type profiles.

New method classifies reticulocytes from red blood cells without labels.

problem Classifying reticulocytes from mature red blood cells without fluorescent labels.
method Unsupervised machine learning on morpho-rheological markers.
result Promising results in classifying reticulocytes from mature red blood cells.

For a finite family of 3-dimensional almost contact metric manifolds with closed the structure form ηη is described a construction of an almost contact metric manifold, where the members of the family are building blocks - cells. Obtained manifold share many properties of cells. One of the more important are nullity c…

2012-03-21abs ↗pdf ↗

HSSE framework embeds single-cell RNA-seq data at multiple scales.

problem Capturing heterogeneous local structure in single-cell RNA-seq data.
method Hierarchical sheaf spectral embedding (HSSE) framework.
result HSSE achieves competitive or improved performance in single-cell RNA-seq data representation learning.

Researchers infer gene activity in dividing cells, accounting for protein inheritance and division history.

problem Inferring protein production kinetics in dividing cells due to protein inheritance and division history.
method Adapted conditional normalizing flows to approximate intractable likelihoods from simulated data.
result Glc3 gene is mostly inactive under stress, with brief and transient expression.

SimCD simultaneously clusters cells and identifies differential gene expression in scRNA-seq data.

problem Separate clustering and differential expression analysis for scRNA-seq data leads to suboptimal results.
method Develops SimCD, a unified hierarchical gamma-negative binomial model for simultaneous cell clustering and differential expression analysis.
result SimCD outperforms existing methods in discovering cell clusters and capturing dynamic expression changes.

We construct a small regular cellular decomposition of the Fulton MacPherson operad FM2FM_2 that is compatible with the operad composition. The cells are indexed by trees with edges of two colors and vertices labelled by cells of the cacti operad. We compute the generating functions counting the cells, that are algebrai…

2019-06-18abs ↗pdf ↗

The moduli space of Riemann surfaces with at least two punctures can be decomposed into a cell complex by using a particular family of ribbon graphs called Nakamura graphs. We distinguish the moduli space with all punctures labelled from that with a single labelled puncture. In both cases, we describe a cell decomposit…

2015-07-10abs ↗pdf ↗

Neural network predicts electrochemical cell faults with 53% less error.

problem Predicting faults in electrochemical cells to avoid safety hazards and reduce costs.
method Self-supervised encoder-decoder neural network that learns degradation from operating conditions.
result Predicted voltage with 53% less error than parametric models, 64% faster fault prediction.

New system constructs cell-type taxonomy across multiple samples.

problem Challenges in matching clusters from different datasets.
method Combines Optimal Transport with Relaxed Marginal Constraints (OT-RMC) for simultaneous alignment of clusters across multiple samples.
result Highly accurate annotation of cell types and sample-level feature extraction.

Model shows how capital accumulation can lead to poverty traps and well-being states.

problem Capital accumulation and its effects on poverty and well-being.
method Stochastic Solow growth model with sigmoidal saving fraction and bimodal steady state distribution.
result Existence of poverty trap with fluctuation-driven transitions between poverty and well-being states.

SMAI framework tests and integrates single-cell data alignability.

problem Lack of a rigorous statistical test for alignability and distortion during alignment.
method Spectral manifold alignment and inference (SMAI) framework.
result SMAI outperforms existing methods in alignability testing and integration.

We offer the following explanation of the statement of the Kuratowski graph planarity criterion and of 6/7 of the statement of the Robertson-Seymour-Thomas intrinsic linking criterion. Let us call a cell complex 'dichotomial' if to every cell there corresponds a unique cell with the complementary set of vertices. Then …

2011-03-28abs ↗pdf ↗