scholarly journals Biological function through network topology: a survey of the human diseasome

2012 ◽  
Vol 11 (6) ◽  
pp. 522-532 ◽  
Author(s):  
V. Janjic ◽  
N. Przulj
Keyword(s):  
Network Topology ◽  
Biological Function

scholarly journals Optimal Network Alignment with Graphlet Degree Vectors

2010 ◽  
Vol 9 ◽  
pp. CIN.S4744 ◽  
Author(s):  
Tijana Milenković ◽  
Weng Leong Ng ◽  
Wayne Hayes ◽  
NatašA PržUlj
Keyword(s):  
Cost Function ◽  
Network Topology ◽  
Biological Networks ◽  
Phylogenetic Trees ◽  
Biological Function ◽  
Network Alignment ◽  
New Method ◽  
Biological Information ◽  
Global Alignment ◽  
Sequence Alignments

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

scholarly journals Topological network alignment uncovers biological function and phylogeny

2010 ◽  
Vol 7 (50) ◽  
pp. 1341-1354 ◽  
Author(s):  
Oleksii Kuchaiev ◽  
Tijana Milenković ◽  
Vesna Memišević ◽  
Wayne Hayes ◽  
Nataša Pržulj
Keyword(s):  
Network Topology ◽  
Biological Networks ◽  
Biological Function ◽  
Protein Interaction Networks ◽  
Phylogenetic Information ◽  
Protein Protein Interaction ◽  
Species Phylogeny ◽  
Topological Network ◽  
Protein Protein Interaction Networks ◽  
Life On Earth

Sequence comparison and alignment has had an enormous impact on our understanding of evolution, biology and disease. Comparison and alignment of biological networks will probably have a similar impact. Existing network alignments use information external to the networks, such as sequence, because no good algorithm for purely topological alignment has yet been devised. In this paper, we present a novel algorithm based solely on network topology, that can be used to align any two networks. We apply it to biological networks to produce by far the most complete topological alignments of biological networks to date. We demonstrate that both species phylogeny and detailed biological function of individual proteins can be extracted from our alignments. Topology-based alignments have the potential to provide a completely new, independent source of phylogenetic information. Our alignment of the protein–protein interaction networks of two very different species—yeast and human—indicate that even distant species share a surprising amount of network topology, suggesting broad similarities in internal cellular wiring across all life on Earth.

scholarly journals Finding gene network topologies for given biological function with recurrent neural network

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jingxiang Shen ◽  
Feng Liu ◽  
Yuhai Tu ◽  
Chao Tang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Topology ◽  
Biological Function ◽  
Biochemical Networks ◽  
Perturbative Method ◽  
Complex Functions ◽  
Network Topologies ◽  
And Function ◽  
The Hill

AbstractSearching for possible biochemical networks that perform a certain function is a challenge in systems biology. For simple functions and small networks, this can be achieved through an exhaustive search of the network topology space. However, it is difficult to scale this approach up to larger networks and more complex functions. Here we tackle this problem by training a recurrent neural network (RNN) to perform the desired function. By developing a systematic perturbative method to interrogate the successfully trained RNNs, we are able to distill the underlying regulatory network among the biological elements (genes, proteins, etc.). Furthermore, we show several cases where the regulation networks found by RNN can achieve the desired biological function when its edges are expressed by more realistic response functions, such as the Hill-function. This method can be used to link topology and function by helping uncover the regulation logic and network topology for complex tasks.

Sobre el concepto de función en biología. Historia y problemas recientes

2010 ◽  
Vol 16 ◽  
Author(s):  
Andrés L. Jaume
Keyword(s):  
Biological Function ◽  
Mechanistic Explanation ◽  
Functional Explanation ◽  
Function Concept ◽  
Philosophical Thinking ◽  
Systemic Theory ◽  
Points Of View

RESUMENEl presente artículo analiza las diferentes teorías que sobre el concepto de función se han vertido en los últimos cuarenta años y sus problemas. Respecto de los dos grandes enfoques (histórico-etiológico y sistémico) se sostiene que el primero, pese a su hegemonía histórica, presenta considerables dificultades y que la reflexión actual se centra cada vez más en la perspectiva sistémica. Esta última puede enfrentarse mejor a los diversos problemas que genera el concepto de función biológica y es siempre preferible.PALABRAS CLAVEFUNCIÓN BIOLÓGICA, FUNCIÓN SISTéMICA, EXPLICACIÓN FUNCIONAL, EXPLICACIÓN BASADA EN MECANISMOS, TELEOLOGíAABSTRACTThis paper analyzes the different theories on biological function and the problems they brought up over the last forty years. Concerning the two most important points of view on functions (aetiological theory and systemic theory) I hold that the aetiological theory, despite its historical hegemony, presents substantial difficulties and that the present philosophical thinking is centred on systemic theories. Systemic theories are capable of solving the various problems generated by the biological function concept which is preferable.KEYWORDSBIOLOGICAL FUNCTION, SySTEMIC FUNCTION, FUNCTIONAL EXPLANATION, MECHANISTIC EXPLANATION TELEOLOGY

Passive mode discovery of network topology

2014 ◽  
Author(s):  
Lisheng Huang ◽  
Mingyong Yin ◽  
Changchun Li ◽  
Xin Wang
Keyword(s):  
Network Topology ◽  
Passive Mode
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