Spatial organization and genetic information in brain development

1988 ◽  
Vol 59 (1) ◽  
pp. 13-21 ◽  
Author(s):  
A. Gierer
2020 ◽  
Vol 139 (4) ◽  
pp. 361-370
Author(s):  
Jürgen Jost

AbstractIn computer science, we can theoretically neatly separate transmission and processing of information, hardware and software, and programs and their inputs. This is much more intricate in biology. Nevertheless, I argue that Shannon’s concept of information is useful in biology, although its application is not as straightforward as many people think. In fact, the recently developed theory of information decomposition can shed much light on the complementarity between coding and regulatory, or internal and environmental information. The key challenge that we formulate in this contribution is to understand how genetic information and external factors combine to create an organism, and conversely how the genome has learned in the course of evolution how to harness the environment, and analogously how coding, regulation and spatial organization interact in cellular processes.


Nature ◽  
2010 ◽  
Vol 466 (7302) ◽  
pp. 77-81 ◽  
Author(s):  
Paula Montero Llopis ◽  
Audrey F. Jackson ◽  
Oleksii Sliusarenko ◽  
Ivan Surovtsev ◽  
Jennifer Heinritz ◽  
...  

Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.


2015 ◽  
Vol 57 ◽  
pp. 189-201 ◽  
Author(s):  
Jay Shankar ◽  
Cecile Boscher ◽  
Ivan R. Nabi

Spatial organization of the plasma membrane is an essential feature of the cellular response to external stimuli. Receptor organization at the cell surface mediates transmission of extracellular stimuli to intracellular signalling molecules and effectors that impact various cellular processes including cell differentiation, metabolism, growth, migration and apoptosis. Membrane domains include morphologically distinct plasma membrane invaginations such as clathrin-coated pits and caveolae, but also less well-defined domains such as lipid rafts and the galectin lattice. In the present chapter, we will discuss interaction between caveolae, lipid rafts and the galectin lattice in the control of cancer cell signalling.


2009 ◽  
Vol 42 (19) ◽  
pp. 11
Author(s):  
MARY ELLEN SCHNEIDER
Keyword(s):  

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