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Biology subjects

Matyjaszkiewicz, A.

Publications and source records attributed to Matyjaszkiewicz, A..

2 recordsLinked to original sources

LimbLab: Pipeline for 3D Analysis and Visualisation of Limb Bud Gene Expression

MotivationAlthough some aspects of limb development can be treated as a 2D problem, a true understanding of the morphogenesis and patterning requires 3D analysis. Since the data on gene expression patterns are largely static 3D image stacks, a major challenge is an efficeint pipeline for staging each data-set, and then aligning and warping the data into a standard atlas for convenient visualisation. ResultsWe present a novel bioinformatic pipeline tailored for 3D visualization and analysis of developing limb buds. The pipeline integrates key steps such as data acquisition, volume cleaning, surface extraction, staging, alignment, and advanced visualization techniques. Its modular design allows researchers to customize workflows while maintaining compatibility with tools such as Fiji and Vedo. Our results highlight the pipelines effectiveness in managing complex 3D gene expression data, enhancing the accuracy and reproducibility of limb development studies. Availability and ImplementationLimbLab is released under the MIT license. The pipeline is implemented in Python and is available as an open-source package. It can be easily installed via pip and is accompanied by comprehensive documentation (https://limblab.embl.es/) to support users at various levels of expertise. The pipeline can be accessed and downloaded at https://github.com/LauAvinyo/limblab.

bioinformatics↗

LimbNET: collaborative platform for simulating spatial patterns of gene networks in limb development

Successful computational modelling of complex biological phenomena will depend on the seamless sharing of models and hypotheses among researchers of all backgrounds - experimental and theoretical. LimbNET, a new online tool for modelling, simulating and visualising spatiotemporal patterning in limb development, aims to facilitate this process within the limb development community. LimbNET enables remote users to define and simulate arbitrary gene regulatory network (GRN) models of 2D spatiotemporal developmental patterning processes. Researchers can test and compare each others hypotheses - GRNs and predicted spatiotemporal patterns - within a common framework. A database of previously created models empowers users to simulate, explore, and extend each others work. Spatiotemporally-varying gene expression intensities, derived from image-based data, are mapped into a standardised computational description of limb growth, integrated within our modelling framework. This enables direct comparison not only between datasets but between data and simulation outputs, closing the feedback loop between experiments and simulation via parameter optimisation. All functionality is accessible through a web browser, requiring no special software, and opening the field of image-driven modelling to the full scientific community.

systems biology↗