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At least 469 records · Page 26Linked to original sources
PubMed2004

Computer control of pH and DO in a laboratory fermenter using a neural network technique.

In this contribution, the advantages of the artificial neural network approach to the identification and control of a laboratory-scale biochemical reactor are demonstrated. It is very important to be able to maintain the levels of two process variables, pH and dissolved oxygen (DO) concentration, over the course of fermentation in biosystems control. A PC-supported, fully automated, multi-task control system has been designed and built by the authors. Forward and inverse neural process models are used to identify and control both the pH and the DO concentration in a fermenter containing a Saccharomyces cerevisiae based-culture. The models are trained off-line, using a modified back-propagation algorithm based on conjugate gradients. The inverse neural controller is augmented by a new adaptive term that results in a system with robust performance. Experimental results have confirmed that the regulatory and tracking performances of the control system proposed are good.

Algorithms↗
PubMed2004

Robotics in vascular surgery.

The procedure for surgical correction of aortic disease has gone relatively unchanged over the last 50 years, requiring a xiphoid pubic incision as well as shifting of the abdominal viscera. These maneuvers produce significant pathophysiologic changes that consequently affect intraoperative and postoperative care and recovery. In approaching minimally invasive aortic surgery, advances in computer-enhanced technology have the potential to revolutionize aortic surgery and improve patient safety. A MEDLINE search specific to robotic aortic vascular procedures was performed and produced 7 articles (3 animal model and 4 clinical application). Robotically assisted technology became available for use in 2000. Since that time, computer-enhanced technology for aortic anastomoses has been applied successfully in the animal model. Early application in the clinical setting for aortoiliac disease also has been successfully initiated. Robotic technology provides the vascular surgeon with the ability to perform the delicate tissue handling necessary for aortic procedures. Based on their knowledge of current procedures, surgeons must redesign their surgical strategies to adapt to this computer-enhanced methodology.

Anastomosis, Surgical↗
PubMed2005

A review on the integration of artificial intelligence into coastal modeling.

With the development of computing technology, mechanistic models are often employed to simulate processes in coastal environments. However, these predictive tools are inevitably highly specialized, involving certain assumptions and/or limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the underlying theories. This results in significant constraints on their manipulation as well as large gaps in understanding and expectations between the developers and practitioners of a model. The recent advancements in artificial intelligence (AI) technologies are making it possible to integrate machine learning capabilities into numerical modeling systems in order to bridge the gaps and lessen the demands on human experts. The objective of this paper is to review the state-of-the-art in the integration of different AI technologies into coastal modeling. The algorithms and methods studied include knowledge-based systems, genetic algorithms, artificial neural networks, and fuzzy inference systems. More focus is given to knowledge-based systems, which have apparent advantages over the others in allowing more transparent transfers of knowledge in the use of models and in furnishing the intelligent manipulation of calibration parameters. Of course, the other AI methods also have their individual contributions towards accurate and reliable predictions of coastal processes. The integrated model might be very powerful, since the advantages of each technique can be combined.

Artificial Intelligence↗
PubMed2006

The Helix: a multi-modal tactile stimulator for human functional neuroimaging.

In order to expand the repertoire of somatosensory functions that can be effectively studied through functional MRI, we have developed a tactile stimulator which can deliver rich and varied combinations of stimulation that simulate natural tactile exploration. The system is computer controlled and compatible with an MRI environment. Complex aspects of somesthesis can thus be studied independent of confounds introduced by motor activity or problems with precision, accuracy or reproducibility of stimulus delivery.

Brain Mapping↗
PubMed1999

Optimal electron and combined electron and photon therapy in the phase space of complication-free cure.

The possibility of using intensity-modulated high-energy electrons beams alone or in combination with photon beams to treat tumours located at depths from 5 cm to 25 cm has been investigated. A radiobiologically based optimization algorithm using the probability of complication-free tumour control has been used to calculate the optimal dose distributions. Two different target volumes have been used; one advanced cervical cancer with locally involved lymph nodes and one astrocytoma in the upper brain hemisphere. Treatments with only electron beams and also combinations between electron and photon beams have been investigated. The dependence of the expected treatment outcome on the beam energy and directions was investigated, and to some extent on the number of beam portals. It is shown that the beam direction intervals resulting in a high expected treatment outcome increase with increasing electron energy and also with some electron-photon combinations. For an eccentrically placed, not too deeply situated tumour surrounded by sensitive normal tissue it is shown that the expected treatment outcome can be improved by using electron beams in combination with photon beams compared with using two photon beams, and using two electron beams results in almost as high an expected treatment outcome. The possibility of improving the dose conformity from electron beams by adding photon fields parallel or orthogonal to the electron beams is demonstrated.

Algorithms↗
PubMed2000

Genetic network inference: from co-expression clustering to reverse engineering.

MOTIVATION: Advances in molecular biological, analytical and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-cluster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e. who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting and bioengineering.

Animals↗
PubMed1998

Computer assisted knee replacement.

Accurate alignment of knee implants is essential for the success of total knee replacement. Although mechanical alignment guides have been designed to improve alignment accuracy, there are several fundamental limitations of this technology that will inhibit additional improvements. Various computer assisted techniques have been developed to examine the potential to install knee implants more accurately and consistently than can be done with mechanical guides. For example, computer integrated instrumentation incorporates highly accurate measurement devices to locate joint centers, track surgical tools, and align prosthetic components. Image guided knee replacement provides a three-dimensional preoperative plan that guides the placement of the cutting blocks and prosthetic components. Robot assisted knee replacement allows one to machine bones accurately without the use of standard cutting blocks. The rationale for the development of computer assisted knee replacement systems is presented, the operation of several different systems is described, the advantages and disadvantages of different approaches are discussed, and areas for future research are suggested.

Arthroplasty, Replacement, Knee↗
PubMed2006

Efficient variant of algorithm FastICA for independent component analysis attaining the Cramér-Rao lower bound.

FastICA is one of the most popular algorithms for independent component analysis (ICA), demixing a set of statistically independent sources that have been mixed linearly. A key question is how accurate the method is for finite data samples. We propose an improved version of the FastICA algorithm which is asymptotically efficient, i.e., its accuracy given by the residual error variance attains the Cramér-Rao lower bound (CRB). The error is thus as small as possible. This result is rigorously proven under the assumption that the probability distribution of the independent signal components belongs to the class of generalized Gaussian (GG) distributions with parameter alpha, denoted GG(alpha) for alpha > 2. We name the algorithm efficient FastICA (EFICA). Computational complexity of a Matlab implementation of the algorithm is shown to be only slightly (about three times) higher than that of the standard symmetric FastICA. Simulations corroborate these claims and show superior performance of the algorithm compared with algorithm JADE of Cardoso and Souloumiac and nonparametric ICA of Boscolo et al. on separating sources with distribution GG (alpha) with arbitrary alpha, as well as on sources with bimodal distribution, and a good performance in separating linearly mixed speech signals.

Algorithms↗
PubMed2005

Automatic selection of representative proteins for bacterial phylogeny.

BACKGROUND: Although there are now about 200 complete bacterial genomes in GenBank, deep bacterial phylogeny remains a difficult problem, due to confounding horizontal gene transfers and other phylogenetic "noise". Previous methods have relied primarily upon biological intuition or manual curation for choosing genomic sequences unlikely to be horizontally transferred, and have given inconsistent phylogenies with poor bootstrap confidence. RESULTS: We describe an algorithm that automatically picks "representative" protein families from entire genomes for use as phylogenetic characters. A representative protein family is one that, taken alone, gives an organismal distance matrix in good agreement with a distance matrix computed from all sufficiently conserved proteins. We then use maximum-likelihood methods to compute phylogenetic trees from a concatenation of representative sequences. We validate the use of representative proteins on a number of small phylogenetic questions with accepted answers. We then use our methodology to compute a robust and well-resolved phylogenetic tree for a diverse set of sequenced bacteria. The tree agrees closely with a recently published tree computed using manually curated proteins, and supports two proposed high-level clades: one containing Actinobacteria, Deinococcus, and Cyanobacteria ("Terrabacteria"), and another containing Planctomycetes and Chlamydiales. CONCLUSION: Representative proteins provide an effective solution to the problem of selecting phylogenetic characters.

Algorithms↗
PubMed1997

A database for evaluating the toxicological risk of pesticides.

This study of Overtox-DB, a computerized database for managing chemical toxicity data, is a product of the application of typical methodologies regarding information science and computer technology. The methodology applied can be reduced to three-basic elements: the collection of requirements, design, and achievement. Overtox-DB was developed by defining technological elements for managing data and its structure and by identifing the procedures and methodologies for data storage, retrieval, distribution, and standardization of many kinds of test data stored in the same format. The program stores data about chemical identification, physical and chemical properties, toxicological tests, mutagenicity, teratogenicity, carcinogenicity, and a bibliography of chemical compounds. Overtox-DB consists of five modules: experimental and bibliographic, data collection, molecular data collection, data search, and data report. The Overtox-DB user responds to a simplified set of query commands and boolean operators that interact with the system to retrieve different toxicological data (the majority of fields are defined as search fields and identify the test system, results of the assays, administration route, dose, etc.). The collected information provides an analytical characterization of biological activities for many compounds and identifies evidence possibly lacking in experimental approaches. Indeed, this database could permit a comparative evaluation with other substances and can be used for structure-activity relationship studies.

Database Management Systems↗
PubMed2003

Integration of distributed multi-analyzer monitoring and control in bioprocessing based on a real-time expert system.

A computer system solution for integration of a distributed bioreactor monitoring and control instrumentation on the laboratory scale is described. Bioreactors equipped with on-line analyzers for mass spectrometry, near-infrared spectroscopy, electrochemical probes and multi-array gas sensors and their respective software were networked through a real-time expert systems platform. The system allowed data transmission of more than 1800 different signals from the instrumentation, including signals from gas sensors, electrodes, spectrometer detectors, balances, flowmeters, etc., and were used for processing and carrying out a number of computational tasks such as partial least-square regression, principal component analysis, artificial neural network modelling, heuristic decision-making and adaptive control. The system was demonstrated on different cultivations/fermentations which illustrated sensor fusion control, multivariate statistical process monitoring, adaptive glucose control and adaptive multivariate control. The performance of these examples showed high operational stability and reliable function and meet typical requirements for production safety and quality.

Algorithms↗
PubMed1999

A potential application to the study of microscopic energy deposition in a solid by means of heavy charged-particle induced photochromic alterations in a tissue-equivalent matrix.

A theoretical study was carried out to investigate the feasibility of using the radiation-induced colour decay of photochromic molecules embedded in a polymer matrix as a probe for studying the microscopic energy deposition of heavy charged particles (HCPs) in a tissue-equivalent solid. The theoretical treatment makes use of the radial dose distribution function as derived from gas-phase physics, together with the effects of the increase in temperature and of matrix degradation on the colour-decay kinetics of the photochromic molecules, according to empirical models derived for the solid state. Bearing in mind the non-stochastic nature of the model, the use of gas-phase physics at the level of radiation interaction, and the fact that some empirical quantities used have been established macroscopically, all factors which signify that extra caution is required in the interpretation of the results, it is shown that when the optimum information retrieval time (after track formation) is considered the technique may be able to resolve differences in the energy deposition pattern by different HCPs in the nanometre range (1-10 nm; material's mass density 1.2 g cm(-3)) from the track axis. Most importantly, though, the present study aims to erect a theoretical framework for the possible application of the technique and to highlight those aspects which are likely to be critical to its practical usage, such as particle type and energy range, and spatial scale and magnitude of the expected effect together with its dependence on time, the physical characteristics of the matrix, and the kinetic behaviour of the type of photochromic molecule studied. Furthermore, it establishes a rationale for interpreting the experimentally observed (if available) colour changes in the HCP track in terms of the microscopic distribution of energy deposition in it.

Benzopyrans↗
PubMed2005

GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA.

BACKGROUND: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence- and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. RESULTS: GANN (available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. CONCLUSION: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

Algorithms↗
PubMed2003

pp-Blast: a "pseudo-parallel" Blast.

We have developed a software called pp-Blast that uses the publicly available Blast package and PVM (parallel virtual machine) to partition a multi-sequence query across a set of nodes with replicated or shared databases. Benchmark tests show that pp-Blast running in a cluster of 14 PCs outperformed conventional Blast running in large servers. In addition, using pp-Blast and the cluster we were able to map all human cDNAs onto the draft of the human genome in less than 6 days. We propose here that the cost/benefit ratio of pp-Blast makes it appropriate for large-scale sequence analysis. The source code and configuration files for pp-Blast are available at http://www.ludwig.org.br/biocomp/tools/pp-blast.

Computing Methodologies↗
PubMed2006

[Studies of methods and exploitation of computer software for mapping interactive genes].

There are six possible types of gene interaction in qualitative traits, namely, complementary, duplicate, cumulative, dominant epistasis, recessive epistasis and inhibiting. In genetic studies, the problem of mapping interactive genes may be met sometimes, but no systematic researches on the methodology and computer software for the mapping of interactive genes have been reported up to date. In this paper, methods for the mapping of interactive genes based on maximum-likelihood estimation and corresponding computer software (IGMapping 1.0) are presented. Computer simulations have shown that the methods proposed can unbiasedly estimate the recombination frequency or linkage distance between a codominant marker and an interactive gene.

Chromosome Mapping↗
PubMed2002

Gene expression profiling diagnosis through DNA molecular computation.

Gene expression profiling is the characterization of cells based on the level of gene activity represented by concentrations of complementary DNA reverse transcribed from messenger RNA. The spectrum of cDNA concentrations, the expression profile, is determined using a DNA microarray. Although this approach is valuable for research, a simpler scheme that would give answers on a shorter time-scale for clinical applications is needed. An Adleman DNA self-assembly computer that would use cDNA as input might be ideal for clinical cell discrimination and a neural network architecture would be appropriate for making the necessary classifications. Preliminary experimental results suggest that expression profiling should be feasible using a DNA neural network that acts directly on cDNA.

Algorithms↗