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We propose a new variational method to isolate points in biological images. As points are fine structures they are difficult to detect by derivative operators computed in the noisy image. In this paper we propose to compute a vector field from the observed intensity so that its divergence explodes at points. As the image could contains spots but also noise and curves where the divergence also blows...
This paper makes two contributions towards the logical modelling of inhibition in metabolic networks. First it exposes the logical inconsistency of an existing state-of-the-art metabolic theory. Then it proposes a new model from which the required hypotheses are consistently inferred. Underlying this work is use of nonmonotonic logic programs to represent and reason about competing inhibitory effects...
In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein's amino acids and whose edges are the interactions between them. Using a graph theory approach, we identify a number of properties of these networks. We compare them to the general scale-free network model and we analyze the existence of nodes with a high interaction level.
This study presents an evolutionary algorithm for locating DNA sequence characters that are diagnostic between closely related groups of species. The algorithm is developed using synthetic data and then tested on biological data from a species of butterfly recently discovered to be a cryptic complex of species. This technique proved to be successful in locating positions that are diagnostic of the...
Microarray technology provides an opportunity for scientists to analyze thousands of gene expression profiles simultaneously. Time-series microarray data are gene expression values generated from microarray experiments within certain time intervals. Scientists can infer gene regulations in a biological system by judging whether two genes present similar gene expression values in microarray time-series...
Due to the high nonlinearity in system models, the large number of kinetics parameters involved, the inadequate measurement data in experiments and the noise pollution, etc., parameter estimation is therefore a challenging problem in systems biology. In this work, sensitivity analysis of model output with respect to model parameters is evaluated using Latin hypercube sampling method. Then, a new objective...
We designed a new genome search tool, basic sequence search by hashing algorithm (BSSHA) bases on basic local alignment search tool (BLAST) and, sequence search and alignment by hashing algorithm (SSAHA) for DNA sequence databases. Preprocess query sequence by making m-letter word list. Sequences in the database are preprocessed by breaking them into k-tuples of k-contiguous bases and hash table is...
Holographic biology found by Chinese Professor Ying-qing Zhang has turned on a new era from the point of view of cognizing the world and has led to a cognitive transform in cognition field and will has broad developmental and applied space. According to systems science and system cognition idea, holographic idea is theoretically explained, it is considered that holographic biomedicine is just a biomedical...
This research integrates rigorous methods of reinforcement learning (RL) and control engineering with a behavioral (ethology) approach to the agent technology. The main outcome is a hybrid architecture for intelligent autonomous agents targeted to the Artificial Life like environments. The architecture adopts several biology concepts and shows that they can provide robust solutions to some areas....
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