ALES: cell lineage analysis and mapping of developmental events

Braun, Volker; Azevedo, Ricardo B. R.; Gumbel, Markus; Agapow, Paul‐Michael; Leroi, Armand M.; Meinzer, Hans-Peter

doi:10.1093/bioinformatics/btg087

Cited by 27 publications

(26 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This question has been raised in species with stereotyped and small lineages such as C. elegans [38]. Investigating more complex and less deterministic lineages will open a completely new field that should adapt methodologies from information and graph theory [39,40].…”

Section: Lineage Tree Reconstruction: Individual Cell Detection and Tmentioning

confidence: 99%

Image analysis for understanding embryo development: a bridge from microscopy to biological insights

Luengo-Oroz

Ledesma-Carbayo

Peyriéras

et al. 2011

Current Opinion in Genetics & Development

View full text Add to dashboard Cite

Section: Lineage Tree Reconstruction: Individual Cell Detection and Tmentioning

confidence: 99%

Image analysis for understanding embryo development: a bridge from microscopy to biological insights

Luengo-Oroz

Ledesma-Carbayo

Peyriéras

et al. 2011

Current Opinion in Genetics & Development

View full text Add to dashboard Cite

“…Examples of recent publications are Silva and Martins (2003); Bernot et al (2004); Platzer and Meinzer (2004) and Siebert and Bockmayr (2008). Dedicated software packages have been developed to support the various types of models (Braun et al, 2003;Albert et al, 2008). Analysis techniques from the electronic field is also applicable as discussed in Dubrova et al (2005).…”

Section: Models Of Dynamic Gene Regulatory Networkmentioning

confidence: 99%

Modelling cell lineage using a meta-Boolean tree model with a relation to gene regulatory networks

Larsson

Wadströmer

Hermanson

et al. 2011

Journal of Theoretical Biology

View full text Add to dashboard Cite

. Modelling cell lineage using a meta-Boolean tree model with a relation to Gene Regulatory Networks. Journal of Theoretical Biology, Elsevier, 2010, 268 (1) This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Modelling cell lineage using a meta-Boolean tree model with a relation to Gene Regulatory Networks AbstractA cell lineage is the ancestral relationship between a group of cells that originate from a single founder cell. For example, in the embryo of the nematode Caenorhabditis elegans an invariant cell lineage has been traced, and with this information at hand it is possible to theoretically model the emergence of different cell types in the lineage, starting from the single fertilized egg. In this report we outline a modelling technique for cell lineage trees, which can be used for the C. elegans embryonic cell lineage but also extended to other lineages. The model takes into account both cell-intrinsic (transcription factor-based) and -extrinsic (extracellular) factors as well as synergies within and between these two types of factors. The model can faithfully recapitulate the entire C. elegans cell lineage, but is also general, i.e. it can be applied to describe any cell lineage. We show that synergy between factors, as well as the use of extrinsic factors, drastically reduce the number of regulatory factors needed for recapitulating the lineage. The model gives indications regarding co-variation of factors, number of involved genes and where in the cell lineage tree that asymmetry might be controlled by external influence. Furthermore, the model is able to emulate other (Boolean, discrete and differential-equation-based) models. As an example, we show that the model can be translated to the language of a previous linear sigmoid-limited concentration-based model (Geard and Wiles, 2005). This means that this latter model also can exhibit synergy effects, and also that the cumbersome iterative technique for parameter estimation previously used is no longer needed. In conclusion, the proposed model is general and simple to use, can be mapped onto other models to extend and simplify their use, and can also be used to indicate where synergy and external influence would reduce the complexity of the regulatory process.

show abstract

“…Braun et al visualized a cell lineage but did not construct the lineage automatically [28]. Yasuda et al designed a semi automatic algorithm for lineaging with human interaction for correcting falsely detected cells [29].…”

Section: Introductionmentioning

confidence: 99%

Cell Lineage Construction of Neural Progenitor Cells

Jayalakshmi¹

2014

IJCA

View full text Add to dashboard Cite

This study aims at automatic construction of cell lineage from time-lapse images of progenitor cells. In order to construct the cell lineage it is very useful to have an efficient cell tracking system. In this paper we have described a system for tracking neural progenitor cells in a sequence of images using multiple matching object method based on modified mahalanobis algorithm. This system produces the results including the position, shape, motility and ancestry of each cell in every frame, which helps in construction of cell lineage. The proposed method has been implemented to the sequence of image frames and the computational results of cell tracking are presented.

show abstract

ALES: cell lineage analysis and mapping of developmental events

Abstract: The program can run on any operating system with a compliant Java 2 environment. Ales is free for academic use and can be downloaded from http://mbi.dkfz-heidelberg.de/mbi/research/cellsim/ales.

Cited by 27 publications

References 27 publications

Image analysis for understanding embryo development: a bridge from microscopy to biological insights

Image analysis for understanding embryo development: a bridge from microscopy to biological insights

Modelling cell lineage using a meta-Boolean tree model with a relation to gene regulatory networks

Cell Lineage Construction of Neural Progenitor Cells

Contact Info

Product

Resources

About