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PubMed2003

Mixed Markov models.

Markov random fields can encode complex probabilistic relationships involving multiple variables and admit efficient procedures for probabilistic inference. However, from a knowledge engineering point of view, these models suffer from a serious limitation. The graph of a Markov field must connect all pairs of variables that are conditionally dependent even for a single choice of values of the other variables. This makes it hard to encode interactions that occur only in a certain context and are absent in all others. Furthermore, the requirement that two variables be connected unless always conditionally independent may lead to excessively dense graphs, obscuring the independencies present among the variables and leading to computationally prohibitive inference algorithms. Mumford [Mumford, D. (1996) in ICIAM 95, eds. Kirchgassner, K., Marenholtz, O. & Mennicken, R. (Akademie Verlag, Berlin), pp. -->233-256-->] proposed an alternative modeling framework where the graph need not be rigid and completely determined a priori. Mixed Markov models contain node-valued random variables that, when instantiated, augment the graph by a set of transient edges. A single joint probability distribution relates the values of regular and node-valued variables. In this article, we study the analytical and computational properties of mixed Markov models. In particular, we show that positive mixed models have a local Markov property that is equivalent to their global factorization. We also describe a computationally efficient procedure for answering probabilistic queries in mixed Markov models.

Journal Article↗
PubMed2004

Genome function--a virus-world view.

By studying viruses one may begin to understand how static genomes can define dynamic processes of development. This talk will describe some of the approaches we are taking, using computer simulations and laboratory experiments, to account for the many molecular-level processes and interactions that occur when a common bacterium, E. coli, is infected by one of its viruses, phage T7. We accounted for processes of phage genome entry, transcription, translation, and DNA replication, including protein-DNA and protein-protein regulatory interactions, and we predicted the dynamics of phage progeny formation. The simulations have enabled us to identify limiting host-cell resources in phage growth, discover novel anti-viral strategies, and suggest frameworks for mining data from global mRNA and protein studies.

Bacteriophage T7↗
PubMed2006

A statistical framework to discover true associations from multiprotein complex pull-down proteomics data sets.

Experimental processes to collect and process proteomics data are increasingly complex, and the computational methods to assess the quality and significance of these data remain unsophisticated. These challenges have led to many biological oversights and computational misconceptions. We developed an empirical Bayes model to analyze multiprotein complex (MPC) proteomics data derived from peptide mass spectrometry detections of purified protein complex pull-down experiments. Using our model and two yeast proteomics data sets, we estimated that there should be an average of about 20 true associations per MPC, almost 10 times as high as was previously estimated. For data sets generated to mimic a real proteome, our model achieved on average 80% sensitivity in detecting true associations, as compared with the 3% sensitivity in previous work, while maintaining a comparable false discovery rate of 0.3%. Cross-examination of our results with protein complexes confirmed by various experimental techniques demonstrates that many true associations that cannot be identified by previous approach are identified by our method.

Algorithms↗
PubMed2005

A geometric invariant-based framework for the analysis of protein conformational space.

MOTIVATION: Characterization of the restricted nature of the protein local conformational space has remained a challenge, thereby necessitating a computationally expensive conformational search in protein modeling. Moreover, owing to the lack of unilateral structural descriptors, conventional data mining techniques, such as clustering and classification, have not been applied in protein structure analysis. RESULTS: We first map the local conformations in a fixed dimensional space by using a carefully selected suite of geometric invariants (GIs) and then reduce the number of dimensions via principal component analysis (PCA). Distribution of the conformations in the space spanned by the first four PCs is visualized as a set of conditional bivariate probability distribution plots, where the peaks correspond to the preferred conformations. The locations of the different canonical structures in the PC-space have been interpreted in the context of the weights of the GIs to the first four PCs. Clustering of the available conformations reveals that the number of preferred local conformations is several orders of magnitude smaller than that suggested previously. SUPPLEMENTARY INFORMATION: www.it.iitb.ac.in/~ashish/bioinfo2005/.

Algorithms↗
PubMed2000

The design and applications of a recursive molecular modeling framework.

In this paper, we present a recursive molecular model suitable for multiresolution analysis in a variety of application areas. Our approach allows ease of use by computer scientists and biologists by proposing a software interface for molecular analysis that hides programming details. We demonstrate that our design is flexible enough for use in desktop analytical applications, in large-scale parallel simulations, and as a server for remote molecular analysis across wide-area networks.

Algorithms↗
PubMed2005

Knowledge representation and sharing using visual semantic modeling for diagnostic medical image databases.

Information technology offers great opportunities for supporting radiologists' expertise in decision support and training. However, this task is challenging due to difficulties in articulating and modeling visual patterns of abnormalities in a computational way. To address these issues, well established approaches to content management and image retrieval have been studied and applied to assist physicians in diagnoses. Unfortunately, most of the studies lack the flexibility of sharing both explicit and tacit knowledge involved in the decision making process, while adapting to each individual's opinion. In this paper, we propose a knowledge repository and exchange framework for diagnostic image databases called "evolutionary system for semantic exchange of information in collaborative environments" (Essence). This framework uses semantic methods to describe visual abnormalities, and offers a solution for tacit knowledge elicitation and exchange in the medical domain. Also, our approach provides a computational and visual mechanism for associating synonymous semantics of visual abnormalities. We conducted several experiments to demonstrate the system's capability of matching synonym terms, and the benefit of using tacit knowledge in improving the meaningfulness of semantic queries.

Artificial Intelligence↗
PubMed2001

The role of computer-assisted simulation in nurse practitioner education.

PURPOSE: To develop a better understanding of the role of computer-assisted simulations (CAS) in nurse practitioner (NP) education by observing 4 pairs of students complete a CAS case. DATA SOURCES: Qualitative observational study of 8 students performing in a computer laboratory and a series of post-observation interviews. Observations were recorded, refined, coded, and quantified based on the theoretical framework of ecological psychology. CONCLUSIONS: Each pair of students established their own "personalities" for the completion of the task. Misinterpretation of information was common and the absence of a live patient interaction affected the reasoning process of the students. The students demonstrated the ability to develop a perspective on the case based on previous nursing experience. Students generally obtained adequate data on which to base differential/final diagnoses. Observations provided information regarding strengths and weaknesses of students and methods used to solve scenarios. IMPLICATIONS FOR PRACTICE: All students agreed that the CAS scenarios were realistic, useful learning experiences, and that the knowledge gained would be transferable to real clinical situations. Such experiences provide useful experience with terminology, sequencing of the examination, and decision-making.

Adult↗
PubMed2002

Structural relationships, thermal properties, and physicochemical characterization of anhydrous and solvated crystalline forms of tetroxoprim.

Six distinct phases of the antibacterial tetroxoprim (TXP) have been isolated by recrystallization from various solvents. These comprise two polymorphs, forms I and II, and four solvates with the following solvents and TXP solvent stoichiometric ratios: chloroform (3:2), water (3:2), methanol (2:1), and ethanol (2:1). Thermal and infrared spectral data showed that forms I and II are enantiotropically related with form II being stable below the transition temperature of 118 degrees C and form I melting at 159 degrees C. The crystal structure of form I contains three crystallographically independent TXP molecules arranged in layers formed by extensive base pairing between the 2,4-diaminopyrimidine rings. This species invariably results upon heating the solvates of TXP. Thermogravimetry and differential scanning calorimetry respectively showed one-step mass losses and progressively increasing desolvation temperatures for the solvates with chloroform, water, ethanol, and methanol. X-ray diffraction studies revealed that the latter three solvates are isostructural, belonging to the class of "isolated site" solvates. Extensive base pairing maintains the common TXP crystalline framework. Thermal data for the desolvation of these phases are reconciled with the observed crystal packing features. Experimental and computed powder X-ray patterns for form I and the solvates with water, methanol, and ethanol are presented.

Anti-Infective Agents↗
PubMed1990

Synaptic dynamics at the neuromuscular junction: mechanisms and models.

During development, the neuromuscular junction passes through a stage of extensive polyinnervation followed by a period of wholesale synapse elimination. In this report we discuss mechanisms and interactions that could mediate many of the key aspects of these important developmental events. Our emphasis is on (1) establishing an overall conceptual framework within which the role of many distinct cellular interactions and molecular factors can be evaluated, and (2) generating computer simulations that systematically test the adequacy of different models in accounting for a wide range of biological data. Our analysis indicates that several relatively simple mechanisms are each capable of explaining a variety of experimental observations. On the other hand, no one mechanism can account for the full spectrum of experimental results. Thus, it is important to consider models that are based on interactions among multiple mechanisms. A potentially powerful combination is one based on (1) a scaffold within the basal lamina or in the postsynaptic membrane which is induced by nerve terminals and which serves to stabilize terminals by a positive feedback mechanism; (2) a sprouting factor whose release by muscle fibers is down-regulated by activity and perhaps other factors; and (3) an intrinsic tendency of motor neurons to withdraw some connections while allowing others to grow.

Animals↗
PubMed2001

Population genetics from an information perspective.

Some basic effects of population genetics are derived governing the occurrences of alleles A(i)and genotypes A(i)A(j)among its members. A principle of extreme physical information (EPI) is used. These effects are (1) the equation of genetic change, (2) Fisher's theorem of partial change, (3) a new uncertainty principle, and (4) the monotonic decrease of Fisher information with time, indicating increased disorder for the population. General conditions of population change are allowed: fitness coefficients w(ij)generally changing with time [except in effect (2)], population randomly or non-randomly mating, and a general number of loci present within each chromosome. EPI is a practical tool for deriving probability laws. It is an outgrowth of a physical process that occurs during any act of measurement. Here the measurement is the random observation of a genotype A(i)A(j). This observation is to be used to estimate the time of the observation, called "evolutionary time". The measurement activity incurs errors in the estimated observation time and fitness value of the observed genotype. By the Cramer-Rao inequality, the product of the two uncertainties must exceed unity [effect (3)]. The Fisher information I in data space is postulated to originate in the space of the genotype where it had some generally larger value J. The EPI principle extremizes the loss of information (I--J) with I=1/2 J. The solution gives rise to effects (1) and (2). Finally, it is shown that effect (4) holds when the population approaches an equilibrium state, e.g. for time values greater than a threshold if fitness coefficients w(ij)are constant. EPI provides a common framework for deriving physical laws and laws of population genetics. The new effects (3) and (4) are confirmed through computer simulation.

Animals↗
PubMed1993

Testing a non-decompositional theory of lemma retrieval in speaking: retrieval of verbs.

Theories of lexical access in speaking differ in whether they assume that words are accessed in a conceptually decomposed or non-decomposed way. In this paper, two experiments are reported that test the non-decompositional theory and computer model proposed by Roelofs (1992a). Subjects had to name pictured actions using verbs and ignore distractor verbs superimposed on the pictures. According to the theory, semantic inhibition should be obtained from distractor cohyponym verbs that are the names of other pictures in the experiment. By contrast, semantic facilitation should be obtained from hyponyms of the target verbs. Both predictions were empirically confirmed, both qualitatively and quantitatively. These findings support the proposed non-decompositional theory and computer model. Furthermore, they refute a recent attempt to deal with a class of retrieval problems within the decompositional framework. Bierwisch and Schreuder (1992) propose to solve the hyperonym problem (Levelt, 1989) by an inhibitory channel in the mental lexicon between a word and its hyperonyms. This predicts semantic inhibition by hyponyms, instead of the observed facilitation.

Adult↗
PubMed1989

The ordering of the nucleotides in DNA: computational problems in molecular biology.

Viewing DNA, RNA and proteins as strings of letters, various algorithms designed for their optimal alignments or their secondary structures have been developed. The results emanating from such sequence editing algorithms are often not correlated with the physio-chemical computations for calculating the detailed atomic coordinates of these molecules. These two aspects are often viewed as separate research entities. Here I attempt to relate various computational aspects of modern molecular biology. In particular, I attempt putting these (along with complementary experimental data) in the framework of a very basic biological question--what fixes the order of the bases in the DNA.

Base Sequence↗
PubMed2003

Bayesian methods for estimating pathogen prevalence within groups of animals from faecal-pat sampling.

Pathogens such as Escherichia coli O157:H7 and Campylobacter spp. have been implicated in outbreaks of food poisoning in the UK and elsewhere. Domestic animals and wildlife are important reservoirs for both of these agents, and cross-contamination from faeces is believed to be responsible for many human outbreaks. Appropriate parameterisation of quantitative microbial-risk models requires representative data at all levels of the food chain. Our focus in this paper is on the early stages of the food chain-specifically, sampling issues which arise at the farm level. We estimated animal-pathogen prevalence from faecal-pat samples using a Bayesian method which reflected the uncertainties inherent in the animal-level prevalence estimates. (Note that prevalence here refers to the percentage of animals shedding the bacteria of interest). The method offers more flexibility than traditional, classical approaches: it allows the incorporation of prior belief, and permits the computation of a variety of distributional and numerical summaries, analogues of which often are not available through a classical framework. The Bayesian technique is illustrated with a number of examples reflecting the effects of a diversity of assumptions about the underlying processes. The technique appears to be both robust and flexible, and is useful when defecation rates in infected and uninfected groups are unequal, where population size is uncertain, and also where the microbiological-test sensitivity is imperfect. We also investigated the determination of the sample size necessary for determining animal-level prevalence from pat samples to within a pre-specified degree of accuracy.

Agriculture↗
PubMed1999

Exploiting inherent relationships in RNN architectures.

We provide the relationship between the learning rate and the slope of a nonlinear activation function of a neuron within the framework of nonlinear modular cascaded systems realised through Recurrent Neural Network (RNN) architectures. This leads to reduction in the computational complexity of learning algorithms which continuously adapt the weights of such architectures, because there is a smaller number of independent parameters to optimise. Results are provided for the Gradient Descent (GD) learning algorithm and the Extended Recursive Least Squares (ERLS) algorithm, using a general nonlinear activation function of a neuron. The results obtained degenerate into the corresponding results for single RNNs, when considering only one module in such cascaded systems.

Journal Article↗
PubMed2003

Heterochromatin and complexity: a theoretical approach.

Heterochromatin represents 30% of eukaryotic genome in Drosophila and 15% in humans. Despite extensive research spanning many decades, its evolutionary significance, as well as the forces that guarantee its maintenance, are still elusive. Many theoretical and experimental approaches have led researchers to propose several conceptual frameworks to elucidate the nature of this huge mysterious genetic material and its spreading in all eukaryotic genomes. "Junk DNA" as well as "selfish genetic material" are two examples of such attempts, but several lines of evidence suggest that such explanations are incomplete. In fact, if the selfish DNA hypothesis does not explain the mapping of genetic functions in heterochromatin, then the junk DNA hypothesis is incomplete in describing both emergence of genetic functions and their maintenance in the eukaryotic heterochromatin. Recent developments in the physics of complex systems and mathematical concepts such as fractals provide new conceptual clues to answer several basic questions concerning the emergence of heterochromatin in eukaryotic genomes, its evolutionary significance, the forces that guarantee its maintenance, and its peculiar behavior in the eukaryotic cell. The aim of this paper is to provide a new theoretical framework for the heterochromatin, considering such genetic material in physical terms as a complex adaptive system. We apply some computer calculations to demonstrate the nonlinearity of the flux of genetic information along the phylogenic tree. Fractal dimensions of representative heterochromatic sequences are provided. A theory is proposed in which heterochromatin is considered a system that evolves in a self-organized manner at the edge of cellular and environmental chaos.

Animals↗
PubMed2000

Landscape approaches for determining the ensemble of folding transition states: success and failure hinge on the degree of frustration.

We present a method for determining structural properties of the ensemble of folding transition states from protein simulations. This method relies on thermodynamic quantities (free energies as a function of global reaction coordinates, such as the percentage of native contacts) and not on "kinetic" measurements (rates, transmission coefficients, complete trajectories); consequently, it requires fewer computational resources compared with other approaches, making it more suited to large and complex models. We explain the theoretical framework that underlies this method and use it to clarify the connection between the experimentally determined Phi value, a quantity determined by the ratio of rate and stability changes due to point mutations, and the average structure of the transition state ensemble. To determine the accuracy of this thermodynamic approach, we apply it to minimalist protein models and compare these results with the ones obtained by using the standard experimental procedure for determining Phi values. We show that the accuracy of both methods depends sensitively on the amount of frustration. In particular, the results are similar when applied to models with minimal amounts of frustration, characteristic of rapid-folding, single-domain globular proteins.

Kinetics↗
PubMed2004

Modelling the propagation of terahertz radiation through a tissue simulating phantom.

Terahertz (THz) frequency radiation, 0.1 THz to 20 THz, is being investigated for biomedical imaging applications following the introduction of pulsed THz sources that produce picosecond pulses and function at room temperature. Owing to the broadband nature of the radiation, spectral and temporal information is available from radiation that has interacted with a sample; this information is exploited in the development of biomedical imaging tools and sensors. In this work, models to aid interpretation of broadband THz spectra were developed and evaluated. THz radiation lies on the boundary between regions best considered using a deterministic electromagnetic approach and those better analysed using a stochastic approach incorporating quantum mechanical effects, so two computational models to simulate the propagation of THz radiation in an absorbing medium were compared. The first was a thin film analysis and the second a stochastic Monte Carlo model. The Cole-Cole model was used to predict the variation with frequency of the physical properties of the sample and scattering was neglected. The two models were compared with measurements from a highly absorbing water-based phantom. The Monte Carlo model gave a prediction closer to experiment over 0.1 to 3 THz. Knowledge of the frequency-dependent physical properties, including the scattering characteristics, of the absorbing media is necessary. The thin film model is computationally simple to implement but is restricted by the geometry of the sample it can describe. The Monte Carlo framework, despite being initially more complex, provides greater flexibility to investigate more complicated sample geometries.

Diagnostic Imaging↗
PubMed2006

Effective permeability of porous media containing branching channel networks.

We study the effective permeability of two-dimensional binary systems characterized by a network of branching channels embedded in a uniform matrix material. Channels are assigned a higher permeability than the surrounding matrix and, therefore, serve as preferential pathways for fluid migration. The channel networks are constructed using a nonlooping invasion percolation model. We perform extensive numerical flow simulations to determine the effective permeability tensor of channel-matrix systems with broadly varying network properties. These computed effective permeabilities are then used to systematically investigate the factors that control the permeability upscaling process. The upscaling framework adopted for this study is based on spatial power averaging. We determine the scaling behavior of the averaging exponent omega by analyzing its dependence on three characteristic properties of the channel-matrix system: (i) the channel-matrix permeability contrast; (ii) the fractal dimension of the channel network, df; and (iii) the average tortuosity of spanning paths on the network backbone, tau. The behavior of and the corresponding component of effective permeability in each principal direction (parallel and perpendicular to the network-spanning direction) are compared. The permeability anisotropy ratio is shown to be a clear function of key system properties.

Journal Article↗