Biomedical subjects

J M Carazo

Publications and source records attributed to J M Carazo.

60 records · Page 4Linked to original sources

PubMedDate not supplied

A framework for querying a database for structural information on 3D images of macromolecules: A web-based query-by-content prototype on the BioImage macromolecular server.

Nowadays we are experiencing a remarkable growth in the number of databases that have become accessible over the Web. However, in a certain number of cases, for example, in the case of BioImage, this information is not of a textual nature, thus posing new challenges in the design of tools to handle these data. In this work, we concentrate on the development of new mechanisms aimed at "querying" these databases of complex data sets by their intrinsic content, rather than by their textual annotations only. We concentrate our efforts on a subset of BioImage containing 3D images (volumes) of biological macromolecules, implementing a first prototype of a "query-by-content" system. In the context of databases of complex data types the term query-by-content makes reference to those data modeling techniques in which user-defined functions aim at "understanding" (to some extent) the informational content of the data sets. In these systems the matching criteria introduced by the user are related to intrinsic features concerning the 3D images themselves, hence, complementing traditional queries by textual key words only. Efficient computational algorithms are required in order to "extract" structural information of the 3D images prior to storing them in the database. Also, easy-to-use interfaces should be implemented in order to obtain feedback from the expert. Our query-by-content prototype is used to construct a concrete query, making use of basic structural features, which are then evaluated over a set of three-dimensional images of biological macromolecules. This experimental implementation can be accessed via the Web at the BioImage server in Madrid, at http://www.bioimage.org/qbc/index.html.

Animals↗

PubMedDate not supplied

The BioImage Database Project: organizing multidimensional biological images in an object-relational database.

The BioImage Database Project collects and structures multidimensional data sets recorded by various microscopic techniques relevant to modern life sciences. It provides, as precisely as possible, the circumstances in which the sample was prepared and the data were recorded. It grants access to the actual data and maintains links between related data sets. In order to promote the interdisciplinary approach of modern science, it offers a large set of key words, which covers essentially all aspects of microscopy. Nonspecialists can, therefore, access and retrieve significant information recorded and submitted by specialists in other areas. A key issue of the undertaking is to exploit the available technology and to provide a well-defined yet flexible structure for dealing with data. Its pivotal element is, therefore, a modern object relational database that structures the metadata and ameliorates the provision of a complete service. The BioImage database can be accessed through the Internet.

PubMedDate not supplied

The effect of overabundant projection directions on 3D reconstruction algorithms.

The experimental process of collecting images from macromolecules in an electron microscope is such that it does not allow for prior specification of the angular distribution of the projection images. As a consequence, an uneven distribution of projection directions may occur. Concerns have been raised recently about the behavior of 3D reconstruction algorithms for the case of unevenly distributed projections. It has been illustrated on experimental data that in the case of a heavily uneven distribution of projection directions some algorithms tend to elongate the reconstructed volumes along the overloaded direction so much as to make a quantitative biological analysis impossible. In answer to these concerns we have developed a strategy for quantitative comparison and optimization of 3D reconstruction algorithms. We apply this strategy to quantitatively analyze algebraic reconstruction techniques (ART) with blobs, simultaneous iterative reconstruction techniques (SIRT) with voxels, and weighted backprojection (WBP). We show that the elongation artifacts that had been previously reported can be strongly reduced. With our specific choices for the free parameters of the three algorithms, WBP reconstructions tend to be inferior to those obtained with either SIRT or ART and the results obtained with ART are comparable to those with SIRT, but at a very small fraction of the computational cost of SIRT.

Algorithms↗

PubMedDate not supplied

A novel neural network technique for analysis and classification of EM single-particle images.

We propose a novel self-organizing neural network for the unsupervised classification of electron microscopy (EM) images of biological macromolecules. The radical novelty of the algorithm lies in its rigorous mathematical formulation that, starting from a large set of possibly very noisy input data, finds a set of "representative" data items, organized onto an ordered output map, such that the probability density of this set of representative items resembles at its possible best the probability density of the input data. In a way, it summarizes large amounts of information into a concise description that rigorously keeps the basic pattern of the input data distribution. In this application to the field of three-dimensional EM of single particles, two different data sets have been used; one comprised 2458 rotational power spectra of individual negative stain images of the G40P helicase of Bacillus subtilis bacteriophage SPP1, and the other contained 2822 cryoelectron images of SV40 large T-antigen. Our experimental results prove that this technique is indeed very successful, providing the user with the capability of exploring complex patterns in a succinct, informative, and objective manner. The above facts, together with the consideration that the integration of this new algorithm with commonly used software packages is immediate, prompt us to propose it as a valuable new tool in the analysis of large collections of noisy data.

Algorithms↗

PubMedDate not supplied

Three-dimensional reconstruction of the sevenfolded form of Bacillus subtilis Gro EL Chaperonin.

Bacillus subtilis grown at 42 degrees C produces a major form of Gro EL-like chaperonin that has been analyzed by electron microscopy. Most of the views show a clear sevenfold symmetry when studied by rotational analysis. The particles were classified into defined families by multivariate analysis and supervised fuzzy-set classification methods, and those belonging to a sevenfold family were averaged to produce a two-dimensional representative projection. These selected particles were then used, when titled by 55 degrees in the microscope goniometer stage, as the starting projections for a three-dimensional reconstruction protocol based on the random conical tilt series method. The resulting reconstruction shows the Gro EL-like chaperonin from B. subtilis as a cylindrical body with seven well defined lobules arranged almost parallel to the longitudinal axis of the particle. There is a channel that is placed along this axis and appears fully open in both sides. The geometry of the channel is polar and presents differences in both faces of the particle.

Bacillus subtilis↗

PubMedDate not supplied

FEMME database: topologic and geometric information of macromolecules.

FEMME (Feature Extraction in a Multi-resolution Macromolecular Environment: http://www.biocomp.cnb.uam.es/FEMME/) database version 1.0 is a new bioinformatics data resource that collects topologic and geometric information obtained from macromolecular structures solved by three-dimensional electron microscopy (3D-EM). Although the FEMME database is focused on medium resolution data, the methodology employed (based on the so-called alpha-shape theory) is applicable to atomic resolution data as well. The alpha-shape representation allows the automatic extraction of structural features from 3D-EM volumes and their subsequent characterisation. FEMME is being populated with 3D-EM data stored in the electron microscopy database EMD-DB (http://www.ebi.ac.uk/msd/). However, and since the number of entries in EMD-DB is still relatively small, FEMME is also being populated in this initial phase with structural data from PDB and PQS databases (http://www.rcsb.org/pdb/ and pqs.ebi.ac.uk/, respectively) whose resolution has been lowered accordingly. Each FEMME entry contains macromolecular geometry and topology information with a detailed description of its structural features. Moreover, FEMME data have facilitated the study and development of a method to retrieve macromolecular structures by their structural content based on the combined use of spin images and neural networks with encouraging results. Therefore, the FEMME database constitutes a powerful tool that provides a uniform and automatic way of analysing volumes coming from 3D-EM that will hopefully help the scientific community to perform wide structural comparisons.

Computational Biology↗