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R B Altman

Publications and source records attributed to R B Altman.

At least 55 records · Page 3Linked to original sources
PubMed1996

Constraining volume by matching the moments of a distance distribution.

The problem of computing a molecular structure from a set of distances arises in the interpretation of NMR data as well as other experimental methods that yield distance information. Techniques for computing structures must find conformations consistent with the distance data. There are often other constraints on the structure that must be satisfied as well. One of the most problematic constraints is the constraint on the total volume occupied by the atoms. In this paper, we use the first two moments (mean and variance) of an estimated distance distribution to constrain the volume of a computed structure. We show that a probabilistic algorithm for matching the first two moments of the estimated distance distribution significantly improves the quality of the solution, especially when the distance information alone is not sufficient to define the structure precisely. We also show that our method is not sensitive to small errors in the estimates of mean and variance of the distance distribution. Finally, we demonstrate the use of this constraint in computing a low-resolution structure of the 30S prokaryotic ribosomal subunit. Quantitative analysis of our results allows us to assess the information content contained in constraints on volume, and to show that in some cases addition of a volume constraint adds information roughly equivalent to doubling the number of input distances. Our results also demonstrate the flexibility of probabilistic representations of structural constraints, and the importance of including volume information to constrain structural computations-especially in the case of sparse data.

Algorithms↗
PubMed1996

Computational methods for defining the allowed conformational space of 16S rRNA based on chemical footprinting data.

Structural models for 16S ribosomal RNA have been proposed based on combinations of crosslinking, chemical protection, shape, and phylogenetic evidence. These models have been based for the most part on independent data sets and different sets of modeling assumptions. In order to evaluate such models meaningfully, methods are required to explicitly model the spatial certainty with which individual structural components are positioned by specific data sets. In this report, we use a constraint satisfaction algorithm to explicitly assess the location of the secondary structural elements of the 16S RNA, as well as the certainty with which these elements can be positioned. The algorithm initially assumes that these helical elements can occupy any position and orientation and then systematically eliminates those positions and orientations that do not satisfy formally parameterized interpretations of structural constraints. Using a conservative interpretation of the hydroxyl radical footprinting data, the positions of the ribosomal proteins as defined by neutron diffraction studies, and the secondary structure of 16S rRNA, the location of the RNA secondary structural elements can be defined with an average precision of 25 A (ranging from 12.8 to 56.3 A). The uncertainty in individual helix positions is both heterogeneous and dependent upon the number of constraints imposed on the helix. The topology of the resulting model is consistent with previous models based on independent approaches. The result of our computation is a conservative upper bound on the possible positions of the RNA secondary structural elements allowed by this data set, and provides a suitable starting point for refinement with other sources of data or different sets of modeling assumptions.

Base Sequence↗
PubMed1996

Lamprey: tracking users on the World Wide Web.

Tracking individual web sessions provides valuable information about user behavior. This information can be used for general purpose evaluation of web-based user interfaces to biomedical information systems. To this end, we have developed Lamprey, a tool for doing quantitative and qualitative analysis of Web-based user interfaces. Lamprey can be used from any conforming browser, and does not require modification of server or client software. By rerouting WWW navigation through a centralized filter, Lamprey collects the sequence and timing of hyperlinks used by individual users to move through the web. Instead of providing marginal statistics, it retains the full information required to recreate a user session. We have built Lamprey as a standard Common Gateway Interface (CGI) that works with all standard WWW browsers and servers. In this paper, we describe Lamprey and provide a short demonstration of this approach for evaluating web usage patterns.

Computer Communication Networks↗
PubMed1996

A programming course in bioinformatics for computer and information science students.

We have created a course entitled "Representations and Algorithms for Computational Molecular Biology" with three specific goals in mind. First, we want to provide a technical introduction for computer science and medical information science students to the challenges of computing with molecular biology data, particularly the advantages of having easy access to real-world data sets. Second, we want to equip the students with the skills required of productive research assistants in molecular biology computing research projects. Finally, we want to provide a showcase for local investigators to describe their work in the context of a course that provide adequate background information. In order to achieve these goals, we have created a programming course, in which three major projects and six smaller assignments are assigned during the quarter. We stress fundamental representations and algorithms during the first part of the course in lectures given by the core faculty, and then have more focused lectures in which faculty research interests are highlighted. The course stressed issues of structural molecular biology, in order to better motivate the critical issues in sequence analysis. The culmination of the course was a challenge to the students to use a version of protein threading to predict which members of a set of unknown sequences were globins. The course was well received, and has been made a core requirement in the Medical Information Sciences program.

Algorithms↗
PubMed1995

Average core structures and variability measures for protein families: application to the immunoglobulins.

A variety of methods are currently available for creating multiple alignments, and these can be used to define and characterize families of related proteins, such as the globins or the immunoglobulins. We have developed a method for using a multiple alignment to identify an average structural "core", a subset of atoms with low structural variation. We show how the means and variances of core-atom positions summarize the commonalities and differences with a family, making them particularly useful in compiling libraries of protein folds. We show further how it is possible to describe the rotation and translation relating two core structures, as in two domains of a multi-domain protein, in a consistent fashion in terms of a "mean" transformation and a deviation about this mean. Once determined, our average core structures (with their implicit measure of structural variation) allow us to define a measure of structural similarity more informative than the usual root-mean-square (RMS) deviation in atomic position, i.e. a "better RMS." Our average structures also permit straightforward comparisons between variation in structure and sequence at each position in a family. We have applied our core-finding methodology in detail to the immunoglobulin family. We find that the structural variability we observe just within the VL and VH domains anticipates the variability that others have observed throughout the whole immunoglobulin superfamily; that a core definition based on sequence conservation, somewhat surprisingly, does not agree with one based on structural similarity; and that the cores of the VL and VH domains vary about 5 degrees in relative orientation across the known structures.

Algorithms↗
PubMed1995

Characterizing the microenvironment surrounding protein sites.

Sites are microenvironments within a biomolecular structure, distinguished by their structural or functional role. A site can be defined by a three-dimensional location and a local neighborhood around this location in which the structure or function exists. We have developed a computer system to facilitate structural analysis (both qualitative and quantitative) of biomolecular sites. Our system automatically examines the spatial distributions of biophysical and biochemical properties, and reports those regions within a site where the distribution of these properties differs significantly from control nonsites. The properties range from simple atom-based characteristics such as charge to polypeptide-based characteristics such as type of secondary structure. Our analysis of sites uses non-sites as controls, providing a baseline for the quantitative assessment of the significance of the features that are uncovered. In this paper, we use radial distributions of properties to study three well-known sites (the binding sites for calcium, the milieu of disulfide bridges, and the serine protease active site). We demonstrate that the system automatically finds many of the previously described features of these sites and augments these features with some new details. In some cases, we cannot confirm the statistical significance of previously reported features. Our results demonstrate that analysis of protein structure is sensitive to assumptions about background distributions, and that these distributions should be considered explicitly during structural analyses.

Binding Sites↗
PubMed1995

Methods for displaying macromolecular structural uncertainty: application to the globins.

Most molecular graphics programs ignore any uncertainty in the atomic coordinates being displayed. Structures are displayed in terms of perfect points, spheres, and lines with no uncertainty. However, all experimental methods for defining structures, and many methods for predicting and comparing structures, associate uncertainties with each atomic coordinate. We have developed graphical representations that highlight these uncertainties. These representations are encapsulated in a new interactive display program, PROTEAND. PROTEAND represents structural uncertainty in three ways: (1) The traditional way: The program shows a collection of structures as superposed and overlapped stick-figure models. (2) Ellipsoids: At each atom position, the program shows an ellipsoid derived from a three-dimensional Gaussian model of uncertainty. This probabilistic model provides additional information about the relationship between atoms that can be displayed as a correlation matrix. (3) Rigid-body volumes: Using clouds of dots, the program can show the range of rigid-body motion of selected substructures, such as individual alpha helices. We illustrate the utility of these display modalities by the applying PROTEAND to the globin family of proteins, and show that certain types of structural variation are best illustrated with different methods of display.

Animals↗
PubMed1995

Using a measure of structural variation to define a core for the globins.

As the database of three-dimensional protein structures expands, it becomes possible to classify related structures into families. Some of these families, such as the globins, have enough members to allow statistical analysis of conserved features. Previously, we have shown that a probabilistic representation based on means and variances can be useful for defining structural cores for large families. These cores contain the subset of atoms that are in essentially the same relative positions in all members of the family. In addition to defining a core, our method creates an ordered list of atoms, ranked by their structural variation. In applying our core-finding procedure to the globins, we find that helices A, B, G and H form a structural core with low variance. These helices fold early in the folding pathway, and superimpose well with helices in the helix-turn-helix repressor protein family. The non-core helices (F and the parts of other helices that interact with it) are associated with the functional differences among the globins, and are encoded within a separate exon. We have also compared the variability measure implicit in our core structures with measures of sequence variability, using a procedure for measuring sequence variability that helps correct for the biased sampling in the databanks. We find, somewhat surprisingly, that sequence variation does not appear to correlate with structural variation.

Algorithms↗
PubMed1995

Characterizing oriented protein structural sites using biochemical properties.

A protein site is a region of a three-dimensional protein structure with a distinguishing functional or structural role. Certain sites recur in different protein structures (for example catalytic sites, calcium binding sites, and some types of turns), but maintain critical shared features. To facilitate the analysis of such protein sites, we have developed a computer system for analyzing the spatial distributions of biochemical properties around a site. The system takes a set of similar sites and a set of control nonsites, and finds differences between them. Specifically, it compares distributions of the properties surrounding the sites with those surrounding the nonsites, and reports statistically significant differences. In this paper, we use our method to analyze the features in the active site of the serine protease enzymes. We compare the use of radial distributions (shells) with 3-D grids (blocks) in the analysis of the active site. We demonstrate three different strategies for focusing attention on significant findings, based on properties of interest, spatial volumes of interest, and on the level of statistical significance. Finally, we show that the program automatically identifies conserved sequential, secondary structural and biophysical features of the serine protease active site, using noncatalytic histidine residues as a control environment.

Algorithms↗
PubMed1994

Constraint satisfaction techniques for modeling large complexes: application to the central domain of 16S ribosomal RNA.

Standard experimental techniques for determining the structure of small to moderately-sized molecules are difficult to apply to large macromolecular complexes. These complexes, consisting of multiple protein and/or nucleic acid components, can contain many thousands of atoms and the experimental techniques used to study them provide relatively sparse structural information with significant measurement uncertainty. Computational technologies are required to reduce the conformational search space and synthesize the data in order to produce the structures or (more usually) sets of structures compatible with the data. In this paper, we show that a method based on the constraint satisfaction paradigm produces a three-dimensional topology for the central domain of the 16S ribosomal RNA that is generally consistent with interactively built models, although differing in significant ways. The modeling incorporates information about secondary structure of the nucleic acid, neutron diffraction data about the relative positions and uncertainties of the proteins, and protection experiments indicating proximities of segments of RNA to specific protein subunits. Unlike previously proposed models, our model contains explicit information about the range of positions for each subunit that are compatible with the data. The system uses a grid search, checks distances in a direction-dependent manner, uses disjunctive distance constraints, and checks for volume overlap violations.

Animals↗
PubMed1994

Finding an average core structure: application to the globins.

We present a procedure for automatically identifying from a set of aligned protein structures a subset of atoms with only a small amount of structural variation, i.e., a core. We apply this procedure to the globin family of proteins. Based purely on the results of the procedure, we show that the globin fold can be divided into two parts. The part with greater structural variation consists of the residues near the heme (the F helix and parts of the G and H helices), and the part with lesser structural variation (the core) forms a structural framework similar to that of the repressor protein (A, B, and E helices and remainder of the G and H helices). Such a division is consistent with many other structural and biochemical findings. In addition, we find further partitions within the core that may have biological significance. Finally, using the structural core of the globin family as a reference point, we have compared structural variation to sequence variation and shown that a core definition based on sequence conservation does not necessarily agree with one based on structural similarity.

Algorithms↗
PubMed1994

Extraction of SNOMED concepts from medical record texts.

Clinicians have traditionally documented patient data using natural language text. With the increasing prevalence of computer systems in health care, an increasing amount of medical record text will be stored electronically. However, for such textual documents to be indexed, shared, and processed adequately by computers, it will be important to be able to identify concepts in the documents using a common medical terminology. Automated methods for extracting concepts in a standard terminology would enhance retrieval and analysis of medical record data. This paper discusses a method for extracting concepts from medical record documents using the medical terminology SNOMED-III (Systematized Nomenclature of Human and Veterinary Medicine, Version III). The technique employs a linear least squares fit that maps training set phrases to SNOMED concepts. This mapping can be used for unknown text inputs in the same domain as the training set to predict SNOMED concepts that are contained in the document. We have implemented the method in the domain of congestive heart failure for history and physical exam texts. Our system has a reasonable response time. We tested the system over a range of thresholds. The system performed with 90% sensitivity and 83% specificity at the lowest threshold, and 42% sensitivity and 99.9% specificity at the highest threshold.

Algorithms↗
PubMed1994

Probabilistic constraint satisfaction: application to radiosurgery.

Although quite successful in a variety of settings, standard optimization approaches can have drawbacks within medical applications. For example, they often provide a single solution which is difficult to explain, or which can not be incrementally modified using secondary "soft" constrains that are difficult to encode within the optimization. In order to address these issues, we have developed a probabilistic optimization technique that allows the user to enter prior probability distributions (Gaussian) for the parameters to be optimized as well as for the constraints on the parameters. Our technique combines the prior distributions with the constraints using Bayes' rule. The algorithm produces not only a set of parameter values, but variances on these values and covariances showing the correlations between parameters. We have applied this method to the problem of planning a radiosurgical ablation of brain tumors. The radiation plan should maximize dose to tumor, minimize dose to surrounding areas, and provide an even distribution of dosage across the tumor. It also should be explainable to and modifiable by the expert physicians based on external considerations. We have compared the results of our method with the standard linear programming approach.

Humans↗
PubMed1993

Probabilistic structure calculations: a three-dimensional tRNA structure from sequence correlation data.

Algorithms based on probability theory can address issues of uncertainty directly through their representational framework and their theory for data combination. In this paper, we discuss the advantages of probabilistic formulations for molecular-structure calculations, describe one implementation of such a formulation, and show its performance on a data set derived from analysis of the statistical correlations within a set of aligned transfer RNA sequences. By assigning reasonable physical interpretations to certain statistical correlations, we are able to calculate three-dimensional structures for tRNA from a random starting structure. The constraints that we use are associated with different variances, and so their effects are not uniform, and must be reconciled by a probabilistic algorithm to yield the most likely structure. As might be predicted, the uncertainty in the position for each base is a function of both the number and strength of the constraints, and is reflected in the variances in atomic position calculated by the algorithm. For example, the hinge region in the tRNA is shown to be the most uncertain. In addition, the algorithm retains information about positional covariation that is useful for understanding the relationships between different parts of the structure. These experiments also demonstrate that we can define a single-sphere representation for each base that is useful for nucleic acid structural calculations in the same way that alpha-carbon representations are useful for protein structural calculations.

Algorithms↗
PubMed1993

Probabilistic constraint satisfaction with structural models: application to organ modeling by radial contours.

One of the key challenges within medical information sciences is the development of useful models for biological structure and its variability. Many biomedical problems involve the elucidation of structure (for example, from experimental data or from imaging studies), and structural models can often drive the process of inferring precise structure from data. Ideally, model-driven data interpretation combines knowledge about the generic features of a class of biological structures (as contained within a model) with data that provide specific information (often noisy) about a particular instance of the class. In this paper we briefly discuss model-driven determination of biological structure as an example of a structural constraint satisfaction problem. We describe a probabilistic implementation of structural constraint satisfaction, and show that our formulation of a particular organ modeling technology (Radial Contour Models) exhibits promising performance. Our results demonstrate the utility of probabilistic models for the solution of structural constraint satisfaction problems.

Computer Simulation↗
PubMed1990

Sequence-specific 1H NMR assignments and secondary structure in solution of Escherichia coli trp repressor.

Sequence-specific 1H NMR assignments are reported for the active L-tryptophan-bound form of Escherichia coli trp repressor. The repressor is a symmetric dimer of 107 residues per monomer; thus at 25 kDa, this is the largest protein for which such detailed sequence-specific assignments have been made. At this molecular mass the broad line widths of the NMR resonances preclude the use of assignment methods based on 1H-1H scalar coupling. Our assignment strategy centers on two-dimensional nuclear Overhauser spectroscopy (NOESY) of a series of selectively deuterated repressor analogues. A new methodology was developed for analysis of the spectra on the basis of the effects of selective deuteration on cross-peak intensities in the NOESY spectra. A total of 90% of the backbone amide protons have been assigned, and 70% of the alpha and side-chain proton resonances are assigned. The local secondary structure was calculated from sequential and medium-range backbone NOEs with the double-iterated Kalman filter method [Altman, R. B., & Jardetzky, O. (1989) Methods Enzymol. 177, 218-246]. The secondary structure agrees with that of the crystal structure [Schevitz, R., Otwinowski, Z., Joachimiak, A., Lawson, C. L., & Sigler, P. B. (1985) Nature 317, 782], except that the solution state is somewhat more disordered in the DNA binding region and in the N-terminal region of the first alpha-helix. Since the repressor is a symmetric dimer, long-range intersubunit NOEs were distinguished from intrasubunit interactions by formation of heterodimers between two appropriate selectively deuterated proteins and comparison of the resulting NOESY spectrum with that of each selectively deuterated homodimer. Thus, from spectra of three heterodimers, long-range NOEs between eight pairs of residues were identified as intersubunit NOEs, and two additional long-range intrasubunits NOEs were assigned.

Amino Acid Sequence↗
PubMed1988

Heuristic refinement method for the derivation of protein solution structures: validation on cytochrome b562.

A method is described for determining the family of protein structures compatible with solution data obtained primarily from nuclear magnetic resonance (NMR) spectroscopy. Starting with all possible conformations, the method systematically excludes conformations until the remaining structures are only those compatible with the data. The apparent computational intractability of this approach is reduced by assembling the protein in pieces, by considering the protein at several levels of abstraction, by utilizing constraint satisfaction methods to consider only a few atoms at a time, and by utilizing artificial intelligence methods of heuristic control to decide which actions will exclude the most conformations. Example results are presented for simulated NMR data from the known crystal structure of cytochrome b562 (103 residues). For 10 sample backbones an average root-mean-square deviation from the crystal of 4.1 A was found for all alpha-carbon atoms and 2.8 A for helix alpha-carbons alone. The 10 backbones define the family of all structures compatible with the data and provide nearly correct starting structures for adjustment by any of the current structure determination methods.

Computer Systems↗