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Parsimonious covering theory is a formal model of diagnostic reasoning. Diagnostic knowledge is represented in the theory as a network of causal associations, and problem-solving is represented in algorithms that support a hypothesize-and-test inference process. This paper summarizes in informal terms the basic ideas in parsimonious covering theory.
The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews.
The basic underlying problem in reverse engineering of gene regulatory networks from gene expression data is that the expression of a gene encoding the regulator provides only limited information about its protein activity. The proteins, which result from translation, are subject to stringent posttranscriptional control and modification. Often, it is only the modified version of the protein that is capable of activating or repressing its regulatory targets. At present there exists no reliable high-throughput technology to measure the protein activity levels in real-time, and therefore they are, so-to-say, lost in translation. However, these activity levels can be recovered by studying the gene expression of their targets. Here, we describe a computational approach to predict temporal regulator activity levels from the gene expression of its transcriptional targets in a network motif with one regulator and many targets. We consider an example of an SOS repair system, and computationally infer the regulator activity of its master repressor, LexA. The reconstructed activity profile of LexA exhibits a behavior that is similar to the experimentally measured profile of this repressor: after UV irradiation, the amount of LexA substantially decreases within a few minutes, followed by a recovery to its normal level. Our approach can easily be applied to known single-input motifs in other organisms.
History of the study of dissociation begins in the second half of the nineteenth century. It begins in the works of Hughlings Jackson and Pierre Janet, and markedly influences development of psychoanalysis and other psychological trends. According to the modern definition, dissociation represents a disturbance or alteration in the normally integrative functions of identity, memory, or consciousness. Dissociative symptoms occur mainly due to some traumatic events and probably cannot be generally explained on the basis of neurological focal lesion. However, from recent findings, it may be inferred that temporal lobe epileptic activity is important in the generation of dissociative symptoms. Recent findings show that neural networks provide an attractive framework for modeling dissociative mental processes and dissociative mechanisms. In the article we propose a new theoretical connection among neural network models of dissociation, Freeman's model of chaos in the brain and electrophysiological findings regarding dissociative states. Concluding remarks are concerned with connections of dissociation and inter-hemispheric communication.
Extracellular recordings were made in the anterior bank of the parieto-occipital sulcus of two waking monkeys trained to perform fixation tasks in normal illumination or in complete darkness. Of the recorded neurons, 73% (251/343) were responsive to visual stimulation, but their overall organization did not conform to a simple, continuous retinotopic map. Most of the visual neurons showed a high degree of orientation and direction sensitivity, higher than that found in areas V1, V2 and V3A under the same experimental conditions. Whether they had a resolvable receptive field or not, the discharge rate of many neurons in the anterior bank of the parieto-occipital sulcus was influenced by oculomotor activity. The animals were required to execute pursuit or saccadic eye movements in darkness. Saccadic eye movements were found to influence 19% of the neurons tested (29/156); by contrast, pursuit eye movements were without effect (0/64). Saccade responses were direction-tuned and, in several cases, the neuronal discharge started before the onset of eye movement. The animals were also required to gaze, in darkness, at nine different positions on the screen they faced. Of the neurons tested, 59% (102/174) were affected by the direction of gaze. Higher discharge rates were generally observed when the animals looked towards the lower part of the field of view. Given the functional properties of its neurons, its connections with area V3A-where neural signals appropriate for building an objective map of the visual space are present (Galletti and Battaglini, 1989, J. Neurosci., 9, 1112-1125)-and its output to the visuomotor centres involved in the generation of saccades (frontal eye fields and superior colliculus), we infer that the cortex of the anterior bank of the parieto-occipital sulcus might be part of the network involved in the control of gaze in order to locate objects in visual space.
Inflammation is an inherent response of the organism that permits its survival despite constant environmental challenges. The process normally leads to recovery from injury and to healing. However, if targeted destruction and assisted repair are not properly phased, chronic inflammation can result in persistent tissue damage. To better understand the inflammatory process, we recently introduced a profiling methodology to identify common genes involved in bladder inflammation. The method represents a complementation to the classic quantification of inflammation and provides information regarding the early, intermediate, and late events in gene regulation. However, gene profiling fails to describe the molecular pathways and their interconnections involved in the particular inflammatory response. The present work introduces a new statistical technique for inferring functional interconnections between inflammatory pathways underlying classic models of bladder inflammation and permits the modeling of the inflammatory network. This new statistical method is based on variants of cluster analysis, Boolean networking, differential equations, Bayesian networking, and partial correlation. By applying partial correlation analysis, we developed mosaics of gene expression that permitted a global visualization of common and unique pathways elicited by different stimuli. The significance of these processes was tested from both biological and statistical viewpoints. We propose that connective mosaic may represent the necessary simplification step to visualize cDNA array results.
Analogy is important for learning and discovery and is considered a core component of intelligence. We present a computational account of analogical reasoning that is compatible with data we have collected from patients with cortical degeneration of either their frontal or anterior temporal cortices due to frontotemporal lobar degeneration (FTLD). These two patient groups showed different deficits in picture and verbal analogies: frontal lobe FTLD patients tended to make errors due to impairments in working memory and inhibitory abilities, whereas temporal lobe FTLD patients tended to make errors due to semantic memory loss. Using the "Learning and Inference with Schemas and Analogies" model, we provide a specific account of how such deficits may arise within neural networks supporting analogical problem solving.
Our natural language understanding system outputs a list of diseases, findings, and appliances found in a chest x-ray report. The system described in this paper links those diseases and findings that are causally related. Using Bayesian networks to model the conceptual and diagnostic information found in a chest x-ray we are able to infer more specific information about the findings that are linked to diseases.
Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through combination of metabolome and transcriptome data.
The middle meningeal vascular network leaves its traces on the endocranial surface because of the tight relationship between neurocranial development and brain growth. Analysing the endocast of fossil specimens, it is therefore possible to describe the morphology of these structures, leading inferences on the cerebral physiology and metabolism in extinct human groups. In this paper, general features of the meningeal vascular traces are described for specimens included in the Homo erectus, Homo neanderthalensis, and Homo sapiens hypodigms. The complexity of the arterial network is quantified by its fractal dimension, calculated through the box-counting method. Modern humans show significant differences from the other two taxa because of the anterior vascular dominance and the larger fractal dimension. Neither the fractal dimension nor the anterior development are merely associated with cranial size increase. Considering the differences between Neanderthals and modern humans, these results may be interpreted in terms of phylogeny, cerebral functions, or cranial structural network.
MOTIVATION: Owing to the complete sequencing of human and many other genomes, huge amounts of DNA sequence data have been accumulated. In bioinformatics, an important issue is how to predict the complete structure of genes from the genomic DNA sequence, especially the human genome. A crucial part in the gene structure prediction is to determine the precise exon-intron boundaries, i.e. the splice sites, in the coding region. RESULTS: We have developed a dependency graph model to fully capture the intrinsic interdependency between base positions in a splice site. The establishment of dependency between two position is based on a chi2-test from known sample data. To facilitate statistical inference, we have expanded the dependency graph (which is usually a graph with cycles that make probabilistic reasoning very difficult, if not impossible) into a Bayesian network (which is a directed acyclic graph that facilitates statistical reasoning). When compared with the existing models such as weight matrix model, weight array model, maximal dependence decomposition, Cai et al.'s tree model as well as the less-studied second-order and third-order Markov chain models, the expanded Bayesian networks from our dependency graph models perform the best in nearly all the cases studied. AVAILABILITY: Software (a program called DGSplicer) and datasets used are available at http://csrl.ee.nthu.edu.tw/bioinf/ CONTACT: cclu@ee.nthu.edu.tw.
The sequence in the first hypervariable segment (HVS-I) of the control region has been used as a source of evolutionary information in most phylogenetic analyses of mtDNA. Population genetic inference would benefit from a better understanding of the variation in the mtDNA coding region, but, thus far, complete mtDNA sequences have been rare. We determined the nucleotide sequence in the coding region of mtDNA from 121 Finns, by conformation-sensitive gel electrophoresis and subsequent sequencing and by direct sequencing of the D loop. Furthermore, 71 sequences from our previous reports were included, so that the samples represented all the mtDNA haplogroups present in the Finnish population. We found a total of 297 variable sites in the coding region, which allowed the compilation of unambiguous phylogenetic networks. The D loop harbored 104 variable sites, and, in most cases, these could be localized within the coding-region networks, without discrepancies. Interestingly, many homoplasies were detected in the coding region. Nucleotide variation in the rRNA and tRNA genes was 6%, and that in the third nucleotide positions of structural genes amounted to 22% of that in the HVS-I. The complete networks enabled the relationships between the mtDNA haplogroups to be analyzed. Phylogenetic networks based on the entire coding-region sequence in mtDNA provide a rich source for further population genetic studies, and complete sequences make it easier to differentiate between disease-causing mutations and rare polymorphisms.
OBJECTIVES: There is evidence for differential neural alterations within the prefrontal cortex (PFC) in bipolar disorder I (BDI) and schizophrenia that may translate into different cognitive deficits. Our objective was to compare the cognitive profile of stable BDI and schizophrenic patients using neuropsychological tasks which utilize frontal systems but differ in terms of the exact neural circuits and cognitive processes involved. METHODS: We studied 43 patients with BDI, 54 with schizophrenia and 46 matched healthy participants. All participants completed (i) the Wisconsin Card Sorting Test (WCST) which is known to recruit the dorsal and ventral PFC, (ii) the verbal fluency task (VFT), which engages frontal-temporal regions, and (iii) the Stroop Colour Word Test (SWCT) which depends on the integrity of the cingulo-frontal network. A series of multivariate analyses examined differences between the cognitive profiles of BD and schizophrenic patients relative to that of healthy participants controlling for general intellectual ability and gender. RESULTS: Bipolar disorder I patients showed minimal verbal fluency impairment while schizophrenic patients demonstrated marked deficits on this task relative to the control and BDI groups. The two patient groups had comparable performance on the WCST. In the SWCT, schizophrenic patients showed impairment in both congruent and incongruent conditions while BD patients had deficits only in the latter. CONCLUSIONS: Absence of significant verbal fluency abnormalities and by inference dysfunction in the associated fronto-temporal circuitry may distinguish BDI from schizophrenia. Both disorders may show impairment in tasks involving cingulo-frontal networks with evidence of greater cingulate dysfunction in schizophrenia.
NMR signal arising from His 26 N(epsilon)H proton in horse and tuna ferrocytochromes c has been assigned. This His residue is highly conserved in most mitochondrial cytochromes c and X-ray crystallographic studies strongly suggested that its side-chain imidazole participates in an internal hydrogen bond network which is relevant to the stability of the non-helical protein folding near the heme active site. The shift and line width of the assigned signal indicated that this NH hydrogen is indeed involved in an internal hydrogen bond. On the basis of the X-ray crystal structures, the carbonyl oxygen of the residue at 44 is thought to act as a proton-acceptor for this hydrogen. The observation of nuclear Overhauser effect correlation between His 26 C(epsilon)H and Asn 31 main-chain amide NH proton signals in the present proteins also demonstrated the formation of the hydrogen bond between these residues. Consequently, the presence of a unique triad hydrogen bond network in these cytochromes c in solution has been confirmed. Taking advantage of the sensitivity of His 26 N(epsilon)H proton signal to the structural properties of this hydrogen bond network, influences of the presence of high concentration of salt or various concentrations of denaturant on the protein folding were inferred from the analysis of the NMR spectral parameters of the signal.
We argue that current theories of multisensory representations are inconsistent with the existence of a large proportion of multimodal neurons with gain fields and partially shifting receptive fields. Moreover, these theories do not fully resolve the recoding and statistical issues involved in multisensory integration. An alternative theory, which we have recently developed and review here, has important implications for the idea of 'frame of reference' in neural spatial representations. This theory is based on a neural architecture that combines basis functions and attractor dynamics. Basis function units are used to solve the recoding problem, whereas attractor dynamics are used for optimal statistical inferences. This architecture accounts for gain fields and partially shifting receptive fields, which emerge naturally as a result of the network connectivity and dynamics.
LOCtarget is a web server and database that predicts and annotates sub-cellular localization for structural genomics targets; LOCnet is one of the methods used in LOCtarget that can predict sub-cellular localization for all eukaryotic and prokaryotic proteins. Targets are taken from the central registration database for structural genomics, namely, TargetDB. LOCtarget predicts localization through a combination of four different methods: known nuclear localization signals (PredictNLS), homology-based transfer of experimental annotations (LOChom), inference through automatic text analysis of SWISS-PROT keywords (LOCkey) and de novo prediction through a system of neural networks (LOCnet). Additionally, we report predictions from SignalP. The final prediction is based on the method with the highest confidence. The web server can be used to predict sub-cellular localization of proteins from their amino acid sequence. The LOCtarget database currently contains localization predictions for all eukaryotic proteins from TargetDB and is updated every week. The server is available at http://www.rostlab.org/services/LOCtarget/.
Theoretical models of text processing, such as the construction-integration framework, pose fundamental questions about causal inference making that are not easily addressed by behavioral studies. In particular, a common result is that causal relatedness has a different effect on text reading times than on memory for the text: Whereas reading times increase linearly as causal relatedness decreases, memory for the text is best for events that are related by a moderate degree of causal relatedness and is poorer for events with low and high relatedness. Our functional magnetic resonance imaging study of the processing of two-sentence passages that varied in their degree of causal relatedness suggests that the inference process can be analyzed into two components, generation and integration, that are subserved by two large-scale cortical networks (a reasoning system in dorsolateral prefrontal cortex and the right-hemisphere language areas). These two cortical networks, which are distinguishable from the classical left-hemisphere language areas, approximately correspond to the two functional relations observed in the behavioral results.
The presence of hyaluronate in the capsular space of the cat muscle spindle was demonstrated using alcian blue staining at various pHs, the critical electrolyte concentration technique and hyaluronidase treatment. In spindles with intact capsules an extracellular marker, the dye Ruthenium Red, gained access to the capsular space through the gap in the sleeve region, but for a limited distance. In muscle spindles with the capsule nicked, the marker diffused into the capsular space in the equatorial region, revealing a dense network in this space which consisted of globular structures interconnected by thin filaments. Based on their thickness, these filaments were inferred to be hyaluronic acid, and the globular structures were inferred to be protein molecules. Longitudinal diffusion of the dye into the capsular space through the nicked site was limited. The limited diffusion is probably due to electrostatic binding of the dye, which is a hexavalent cation, to negatively charged glycosaminoglycan hyaluronate that is present in the space. The transcapsular potential was measured by use of glass micropipettes filled with 3 M-KCl. The value was 15 mV +/- 4 (average +/- S.D., n = 12; range, 10-20 mV) inside negative. The input resistance and capacitance of the capsule, measured with two independent electrodes, varied widely (1.3-8.0 M omega and 0.5-1.3 nF, n = 4) and the capsule showed marked delayed rectification to outward current pulses. [K+] in the space measured with K+-sensitive resin-filled glass micropipettes was a few millimolar higher than that in the bathing solution. The effects of [K+] and [Ca2+] on impulse activities were examined in spindles with intact capsules or with partially resected capsules. In spindles with intact capsules the effects of [K+] and [Ca2+] were significantly less or negligible compared with those in spindles with the capsule opened. Hyaluronidase (approximately 10(-4) g/ml) added to the bathing solution around nicked capsules significantly reduced both resting and stretch-induced impulse activities in 40-50 min. By this time the capsular space was completely collapsed. An increase in [K+] of the bathing solution from 3.5 to 6 or 8 mM restored these impulse activities. A similar restoring effect was also observed when [Ca2+] in the bathing solution was reduced.(ABSTRACT TRUNCATED AT 400 WORDS)