21 papers · ranked by Valyu relevance
Yi Huang, Joaquin Perez-Schindler, Sanchari Datta, Yijia Christiana Liu + 18 more
Genome-wide association studies (GWAS) have identified thousands of loci associated with cardiometabolic disease, yet translating these associations into regulatory mechanisms, effector genes, and cellular programs remains a major challenge. A key limitation is that genetic effects are often highly context dependent…
Marie Moullet, Tomoya Isobe, Amirhossein Vahidi, Carlo Leonardi + 38 more
Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of tens of thousands of genes at once. However, extracting biological insights from such high-dimensional data remains challenging. To enable downstream analyses, many…
Patrik Christen
—This study explores running times of different ways to program cellular automata in C and C++, i.e. looping through arrays by different means, the effect of structures and objects, and the choice of data structure (array versus vector in C++) and compiler (GNU gcc versus Apple clang). Using arrays instead of vectors…
Russell Z. Kunes, Thomas Walle, Tal Nawy, Dana Pe’er
Factor analysis can drive biological discovery by decomposing single-cell gene expression data into a minimal set of gene programs that correspond to processes executed by cells in a sample. However, matrix factorization methods are prone to technical artifacts and poor factor interpretability. We have developed…
Soroor Hediyeh-zadeh, Holly J. Whitfield, Malvika Kharbanda, Fabiola Curion + 3 more
As single cell molecular data expand, there is an increasing need for algorithms that efficiently query and prioritize gene programs, cell types and states in single-cell sequencing data, particularly in cell atlases. Here we present scDECAF, a statistical learning algorithm to identify cell types, states and programs…
Han Zhang, Binfeng Lu, Aodong Qiu, Gregory F. Cooper + 4 more
Cells within a tissue microenvironment communicate through intricate cell-cell communication (CCC) networks. In this meta-analysis of eight single-cell cohorts encompassing 153 patients and 279 samples, we advance the understanding of CCC networks in colorectal cancers through a novel analytical framework. Employing…
Genaro J. Martinez, Andrew Adamatzky, Guanrong Chen
Cellular automata are arrays of finite state machines that can exist in a finite number of states. These machines update their states simultaneously based on specific local rules that govern their interactions. This framework provides a simple yet powerful model for studying complex systems and emergent behaviors. We…
Robert W Gregg, Panayiotis V Benos, Lenore Cowen
Cellular Potts Models (CPMs) are a popular method to simulate multiscale cellular behaviors because they retain some spatial information like cellular geometry but avoid the computational complexity of a full physics simulation. Their applications are general, but many researchers have focused on using these models to…
Sinan Ozbay, Aditya Parekh, Rohit Singh
The utility of single-cell RNA sequencing (scRNA-seq) is premised on the notion that transcriptional state can faithfully reflect cell phenotype. However, scRNA-seq measurements are noisy and sparse, with individual transcript counts showing limited correlation with cell phenotype markers such as protein expression. To…
Donny Chan, Graham L. Cromar, Billy Taj, John Parkinson
Background With the generation of vast compendia of biological datasets, the challenge is how best to interpret ‘omics data alongside biochemical and other small-scale experiments to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel…
Hratch Baghdassarian, Daniel Dimitrov, Erick Armingol, Julio Saez-Rodriguez + 1 more
In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. While multiple cell-cell communication tools exist, results are specific to the tool of choice, due to the diverse assumptions made across computational frameworks. Moreover, tools are…
Martin Spitznagel, Janis Keuper
Stephen Wolfram proclaimed in his 2003 seminal work "A New Kind Of Science" that simple recursive programs in the form of Cellular Automata (CA) are a promising approach to replace currently used mathematical formalizations, e.g. differential equations, to improve the modeling of complex systems. Over two decades…
Wandi Zhu, Rahul C. Deo, Calum A. MacRae
The full range of cell functions is under-determined in most human diseases. The evidence that somatic cell competition and clonal imbalance play a role in non-neoplastic chronic disease reveal a need for a dedicated effort to explore single cell function if we are to understand the mechanisms by which cell population…
Michele Polese, Mischa Döhler, Falko Dressler, Melike Erol‐Kantarci + 3 more
'Rittwik Jana' 'Raymond Knopp' 'Tommaso Melodia'] 1 ©IEEE 2023. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for…
Stathis Megas, Daniel G. Chen, Krzysztof Polański, Moshe Eliasof + 2 more
perturbation modeling Authors: ['Stathis Megas' 'Daniel G. Chen' 'Krzysztof Polański' 'Moshe Eliasof' 'Carola‐Bibiane Schönlieb' 'Sarah A. Teichmann'] Celcomen leverages a mathematical causality framework to disentangle intra- and intercellular gene regulation programs in spatial transcriptomics and single-cell data…
Elvira Toscano, Elena Cimmino, Fabrizio A. Pennacchio, Patrizia Riccio + 5 more
'Patrizia Riccio' 'Alessandro Poli' 'Yan-Jun Liu' 'Paolo Maiuri' 'Leandra Sepe' 'Giovanni Paolella'] Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues…
Jamshaid A. Shahir, Natalie Stanley, Jeremy E. Purvis
With the growing number of single-cell datasets collected under more complex experimental conditions, there is an opportunity to leverage single-cell variability to reveal deeper insights into how cells respond to perturbations. Many existing approaches rely on discretizing the data into clusters for differential gene…
Ushasi Roy, Tyler Collins, Mohit Kumar Jolly, Parag Katira
| 1 | | Introduction - Collective Cell Migration | 2 | | --- | --- | --- | --- | | 2 | | Factors influencing Collective Cell Migration | 3 | | | 2.1 | Direct Cell-Cell Mechanical Interactions | 3 | | | 2.2 | Direct Cell-Cell Biochemical Interactions | 4 | | | 2.3 | Indirect Cell-Cell Interactions via the Environment |…
Moriah Echlin, Boris Aguilar, Ilya Shmulevich, Alessandro Giuliani
Communication between cells enables the coordination that drives structural and functional complexity in biological systems. Both single and multicellular organisms have evolved diverse communication systems for a range of purposes, including synchronization of behavior, division of labor, and spatial organization.…
Shouguo Gao, Xingmin Feng, Zhijie Wu, Sachiko Kajigaya + 3 more
'Neal S. Young' 'Yan Guo' 'Jinchuan Xing'] Simple Summary CellCall is an R package tool that is used to analyze cell-cell communication based on transcription factor (TF) activities calculated by cell-type specificity of target genes and thus cannot directly handle two-condition comparisons. We developed CellCallEXT to…
Authors not listed
Self-organizing tissues, such as organoids, offer transformative potential beyond healthcare by enabling the sustainable production of advanced materials. Resource scarcity and global warming drive the need for innovative fabrication solutions. This prospective review explores developmental biology as a manufacturing…