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PubMed2004

Towards the automatic generation of biomedical sources schema.

Biologists and physicians need to access biological and medical data for their experimentations and researches. This information is available on the Internet and is scattered over many heterogeneous data sources. Collecting information is consequently tedious, time consuming and must be improved. To cope with this difficulty, our overall objective is to realize a mediator-based system to integrate heterogeneous biomedical data sources. This requires first an automatic generation of source schema, which is the goal of this work. For that, we describe an algorithm which is based on information extraction. It consists of the extraction of meta-information from each source to infer their schema. Our system enables users to access relevant and specific data, which are up-to-date. To solve the semantic heterogeneity of data sources, we are considering the creation of an ontology. Finally, the management of source evolution is discussed

Algorithms↗
PubMedDate not supplied

[Interaction between heterogeneous streams of excitation in the process of fixation and extraction of information in the central nervous system].

Neuronal reactions in the hippocampus and sensorimotor area were recorded in alert rabbits during conditioning to light flashes of different frequency, reinforced by isochronous electro-cutaneous stimulation. Changes of responses to light flashes (CS) as compared with those to an inhibitory stimulus, were observed in the sensorimotor neurones which reacted to the reinforcement by a convergence or frequency-nonspecific type of response, and in the hippocampal neurones reacting to electro-cutaneous stimulation: they were manifested in imitation by CS action of frequency-nonspecific components of response to reinforcement. The results obtained corroborate the concept of appearance in response to a stimulus of heterogeneous excitation flow: modality-specific and modality-nonspecific, as well as of a substantial role of their convergence in the integration of neurones during fixation and reproduction of information in the CNS.

Animals↗
PubMed2006

Computational hyperspectral interferometry for studies of brain function: proof of concept.

Hyperspectral interferometric microscopy uses a unique combination of optics and algorithm design to extract information. Local brain activity rapidly changes local blood flow and red blood cell concentration (absorption) and oxygenation (color). We demonstrate that brain activity evoked during whisker stimulation can be detected with hyperspectral interferometric microscopy to identify the active whisker-barrel cortex in the rat brain. Information about constituent components is extracted across the entire spectral band. Algorithms can be flexibly optimized to discover, detect, quantify, and visualize a wide range of significant biological events, including changes relevant to the diagnosis and treatment of disease.

Animals↗
PubMed1993

Four questions of time to contact: a critical examination of research on interceptive timing.

Four questions concerning the use and perception of time to contact, tc, are identified. (i) Is tc information used in the timing of interceptive actions? (ii) If so, what control strategies are used? (iii) What are the perceptual sources of tc information and which of them do people use? (iv) How is the information extracted by the perceptual systems? Research relevant to these questions is reviewed and analysed. In connection with question (i), theoretical work on the special case of catching a moving object is analysed. It is concluded that treatments of catching which involve the use of tc information provide the best account of timing. In connection with question (ii), two types of control strategy suggested in the literature are identified: an intermittent strategy and a continuous strategy. Evidence for a continuous strategy is reconsidered and shown to be at least as well if not better accounted for by an intermittent strategy. Other empirical evidence for intermittent control is also discussed. In connection with question (iii) a simple unifying method is outlined with which all tc information so far presented in the literature can be derived, and examples are given. The viability of various types of information as sources of tc is examined by considering the errors which would result from their use. Finally, in connection with question (iv) the role of 'looming detectors' in the extraction of tc information is considered. These are frequently proposed as mechanisms for extracting the tc information provided by Lee's optic variable, tau. The analysis provided indicates that, despite the existence of a well-known and popular theory, due mainly to Lee, about how interceptive actions are timed, very little is actually known about perceptual timing. It is not yet certain whether tc information is used in interceptive timing tasks, what kinds of control strategies are involved, what sources of information people use to time their actions, or what perceptual processing is involved in the extraction of tc information.

Feedback↗
PubMed2004

PASBio: predicate-argument structures for event extraction in molecular biology.

BACKGROUND: The exploitation of information extraction (IE), a technology aiming to provide instances of structured representations from free-form text, has been rapidly growing within the molecular biology (MB) research community to keep track of the latest results reported in literature. IE systems have traditionally used shallow syntactic patterns for matching facts in sentences but such approaches appear inadequate to achieve high accuracy in MB event extraction due to complex sentence structure. A consensus in the IE community is emerging on the necessity for exploiting deeper knowledge structures such as through the relations between a verb and its arguments shown by predicate-argument structure (PAS). PAS is of interest as structures typically correspond to events of interest and their participating entities. For this to be realized within IE a key knowledge component is the definition of PAS frames. PAS frames for non-technical domains such as newswire are already being constructed in several projects such as PropBank, VerbNet, and FrameNet. Knowledge from PAS should enable more accurate applications in several areas where sentence understanding is required like machine translation and text summarization. In this article, we explore the need to adapt PAS for the MB domain and specify PAS frames to support IE, as well as outlining the major issues that require consideration in their construction. RESULTS: We introduce PASBio by extending a model based on PropBank to the MB domain. The hypothesis we explore is that PAS holds the key for understanding relationships describing the roles of genes and gene products in mediating their biological functions. We chose predicates describing gene expression, molecular interactions and signal transduction events with the aim of covering a number of research areas in MB. Analysis was performed on sentences containing a set of verbal predicates from MEDLINE and full text journals. Results confirm the necessity to analyze PAS specifically for MB domain. CONCLUSIONS: At present PASBio contains the analyzed PAS of over 30 verbs, publicly available on the Internet for use in advanced applications. In the future we aim to expand the knowledge base to cover more verbs and the nominal form of each predicate.

Cybernetics↗
PubMed2005

Discrete Fourier transform-based analysis of HeLa cell microtubules after ultrasonic exposure.

Cytoskeletal structures can be affected by external factors including ultrasound. Our task was to develop a structure analysis method to evaluate these changes quantitatively. We exposed HeLa cells to continuous ultrasound (1 MHz, 1 and 2 W/cm2, 10 min at 37 degrees C). The microtubules were detected by the monoclonal antibody TU-01/SwAM/FITC, observed in a fluorescence microscope and photographed digitally. The images were processed by "FFT magic" software. The structure analysis is based on frequency domain filtering using discrete Fourier transform. The basic idea is to design filters to extract information describing best the structural changes. The properties of the filter can be enhanced by direction filtering, i.e., extraction of a symmetric angular segment in the frequency domain centered on a zero frequency. The final image is a normalized sum of inverse FFT's of such segmented spectra. We needed a method yielding a single number assigned to the structure, e.g., the ratio of the area of microtubules to the total cell area. Assuming that the image background intensity is constant, we can use thresholding to detect areas occupied by the cells. The information about the area of the microtubules is contained in a wide range of higher intensities. Therefore, we use a gamma correction. The area occupied by microtubules is then considered an area with intensities above the selected threshold. There were tested three different filters to extract information about microtubules. The mathematical method chosen seems sensitive enough for quantitative assessment of changes of the microtubular network.

Fourier Analysis↗
PubMed2004

HYPROSP: a hybrid protein secondary structure prediction algorithm--a knowledge-based approach.

We develop a knowledge-based approach (called PROSP) for protein secondary structure prediction. The knowledge base contains small peptide fragments together with their secondary structural information. A quantitative measure M, called match rate, is defined to measure the amount of structural information that a target protein can extract from the knowledge base. Our experimental results show that proteins with a higher match rate will likely be predicted more accurately based on PROSP. That is, there is roughly a monotone correlation between the prediction accuracy and the amount of structure matching with the knowledge base. To fully utilize the strength of our knowledge base, a hybrid prediction method is proposed as follows: if the match rate of a target protein is at least 80%, we use the extracted information to make the prediction; otherwise, we adopt a popular machine-learning approach. This comprises our hybrid protein structure prediction (HYPROSP) approach. We use the DSSP and EVA data as our datasets and PSIPRED as our underlying machine-learning algorithm. For target proteins with match rate at least 80%, the average Q3 of PROSP is 3.96 and 7.2 better than that of PSIPRED on DSSP and EVA data, respectively.

Algorithms↗
PubMed2000

Lymphoma discrimination by computerized triple matrix analysis of list mode data from three-color flow cytometric immunophenotypes of bone marrow aspirates.

BACKGROUND: The goal of this study was to evaluate a self-learning algorithm for the computer classification of information extracted from flow cytometric immunophenotype list mode files from high-grade non-Hodgkin's lymphoma (NHL), Hodgkin's disease (HD), and multiple myeloma (MM). Materials and Methods Bone marrow aspirates (BMA) were obtained from untreated NHL (n = 51), HD (n = 9), or MM (n = 13) patients. Bone marrow aspirates were not infiltrated in NHL and HD patients as confirmed by thorough histologic and cytologic investigation; however, MM patients showed an infiltration rate >50% by malignant myeloma cells. Peripheral blood leukocyte (PBL) samples were taken from age-matched healthy volunteers (n = 44) as easily available control material. A second control group of 15 healthy volunteers, from whom BMA and PBL samples were available, allowed us to differentiate whether the observed classification results on malignant samples were due to the malignant process or simply to the inherent differences between BMA and PBL. Bone marrow aspirates and PBL were analyzed by the same immunophenotyping antibody panel (CD45/14/20, CD4/8/3, kappa/CD19/5, lambda/CD19/5). The acquired list mode data files were analyzed and classified by the self-learning triple matrix classification algorithms CLASSIF1 following a priori separation of the data into a learning set and unknown test set. After completion of the learning phase, known patient samples were reclassified and unknown samples prospectively classified by the algorithm. RESULTS: Highly discriminatory information was extracted for the various lymphoma entities. The most discriminating information was encountered in antibody binding, antibody binding ratios, and relative antibody surface density parameters of leukocytes rather than in percentage frequencies of discrete leukocyte subpopulations. Samples from healthy controls were classified as normal in 97.2% of the cases, whereas those of NHL, HD, and MM patients were on average correctly classified in 80. 8% of the cases. CONCLUSIONS: Although no detectable lymphoma cells were present in BMA of NHL and HD patients, the CLASSIF1 classification of the immunophenotypes of morphologically normal cells provided a surprisingly good disease discrimination equal or better than that obtained by examining pathological lymph nodes according to the respective literature. The results are suggestive for a lymphoma-related and disease-specific antigen expression shift on normal hematopoietic bone marrow cells that can be used to discriminate the underlying disease (specificity of unspecific changes), i.e., in this case NHL from HD. Multiple myeloma patients were discriminated by changes on malignant as well as on normal bone marrow cells.

Algorithms↗
PubMedDate not supplied

Automatically identifying gene/protein terms in MEDLINE abstracts.

MOTIVATION: Natural language processing (NLP) techniques are used to extract information automatically from computer-readable literature. In biology, the identification of terms corresponding to biological substances (e.g., genes and proteins) is a necessary step that precedes the application of other NLP systems that extract biological information (e.g., protein-protein interactions, gene regulation events, and biochemical pathways). We have developed GPmarkup (for "gene/protein-full name mark up"), a software system that automatically identifies gene/protein terms (i.e., symbols or full names) in MEDLINE abstracts. As a part of marking up process, we also generated automatically a knowledge source of paired gene/protein symbols and full names (e.g., LARD for lymphocyte associated receptor of death) from MEDLINE. We found that many of the pairs in our knowledge source do not appear in the current GenBank database. Therefore our methods may also be used for automatic lexicon generation. RESULTS: GPmarkup has 73% recall and 93% precision in identifying and marking up gene/protein terms in MEDLINE abstracts. AVAILABILITY: A random sample of gene/protein symbols and full names and a sample set of marked up abstracts can be viewed at http://www.cpmc.columbia.edu/homepages/yuh9001/GPmarkup/. Contact. hy52@columbia.edu. Voice: 212-939-7028; fax: 212-666-0140.

Abstracting and Indexing↗
PubMed1999

Automatic extraction of biological information from scientific text: protein-protein interactions.

We describe the basic design of a system for automatic detection of protein-protein interactions extracted from scientific abstracts. By restricting the problem domain and imposing a number of strong assumptions which include pre-specified protein names and a limited set of verbs that represent actions, we show that it is possible to perform accurate information extraction. The performance of the system is evaluated with different cases of real-world interaction networks, including the Drosophila cell cycle control. The results obtained computationally are in good agreement with current biological knowledge and demonstrate the feasibility of developing a fully automated system able to describe networks of protein interactions with sufficient accuracy.

Algorithms↗
PubMed2004

Automated segmentation of human brain MR images using a multi-agent approach.

Image interpretation consists in finding a correspondence between radiometric information and symbolic labeling with respect to specific spatial constraints. It is intrinsically a distributed process in terms of goals to be reached, zones in the image to be processed and methods to be applied. To cope the the difficulty inherent in this process, several information processing steps are required to gradually extract information. In this paper we advocate the use of situated cooperative agents as a framework for managing such steps. Dedicated agent behaviors are dynamically adapted depending on their position in the image, of their topographic relationships and of the radiometric information available. The information collected by the agents is gathered, shared via qualitative maps, or used as soon as available by acquaintances. Incremental refinement of interpretation is obtained through a coarse to fine strategy. Our work is essentially focused on radiometry-based tissue interpretation where knowledge is introduced or extracted at several levels to estimate models for tissue-intensity distribution and to cope with noise, intensity non-uniformity and partial volume effect. Several experiments on phantom and real images were performed. A complete volume can be segmented in less than 5 min with about 0.84% accuracy of the segmented reference. Comparison with other techniques demonstrates the potential interest of our approach for magnetic resonance imaging (MRI) brain scan interpretation.

Artificial Intelligence↗
PubMed1997

Self-organization of firing activities in monkey's motor cortex: trajectory computation from spike signals.

The population vector method has been developed to combine the simultaneous direction-related activities of a population of motor cortical neurons to predict the trajectory of the arm movement. In this article, we consider a self-organizing model of a neural representation of the arm trajectory based on neuronal discharge rates. As self-organizing feature map (SOFM) is used to select the optimal set of weights in the model to determine the contribution of an individual neuron to an overall movement representation. The correspondence between movement directions and discharge patterns of the motor cortical neurons is established in the output map. The topology-preserving property of the SOFM is used to analyze the recorded data of a behaving monkey. The data used in this analysis were taken while the monkey was tracing spirals and doing center-->out movements. The arm trajectory could be well predicted using such a statistical model based on the motor cortex neuronal firing information. The SOFM method is compared with the population vector method, which extracts information related to trajectory by assuming that each cell has a fixed preferred direction during the task. This implies that these cells are acting along lines labeled only for direction. However, extradirectional information is carried in these cell responses. The SOFM has the capability of extracting not only direction-related information but also other parameters that are consistently represented in the activity of the recorded population of cells.

Algorithms↗
PubMed2004

Inter-rater agreement in defining chemical incidents at the National Poisons Information Service, London.

BACKGROUND: National surveillance for chemical incidents is being developed in the UK. It is important to improve the quality of information collected, standardise techniques, and train personnel. OBJECTIVE: To define the extent to which eight National Poison Information Service specialists in poison information agree on the classification of calls received as "chemical incidents" based on the national definition. DESIGN: Blinded, inter-rater reliability measured using the kappa statistic for multiple raters. SETTING: National Poison Information Service and Chemical Incident Response Service, Guy's and St Thomas's NHS Trust, London. PARTICIPANTS: Eight specialists in poison information who are trained and experienced in handling poisons information calls and have been involved in extracting information for surveillance. RESULTS: The overall level of agreement observed was at least 69% greater than expected by chance (kappa statistic). Fire and incidents where chemicals were released within a property had a very good level of agreement with kappa statistic of 83% and 80% respectively. The lowest level of agreement was observed when no one or only one person was exposed to a chemical (33%) and when the chemical was released into the air (48%). CONCLUSION: High levels of agreement were observed. There is a need for more training and improvement in consistency of the data collected by all organisations.

Environmental Exposure↗