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PubMed1994

Role of inhibition in memory retrieval by hippocampal area CA3.

A network model with some general properties of hippocampal area CA3, and the results of its simulation on a massively parallel processor, are described. This network performs the tasks of recent declarative memory including recovery of complete traces from partial cues and recognition of familiarity. Immediate recurrent inhibition is essential for providing sensitivity to small cues while preventing spurious recall. Tonic inhibition seems to set the retrieval speed/accuracy trade-off. Delayed inhibition resets hippocampal activity. The behavior under excessive or deficient inhibition resembles that of amnesics with lesions in brainstem areas known to modulate hippocampal inhibition. The rate of recall and dynamics of inhibition by the model are similar to those inferred to occur in the human hippocampus from unit and evoked potential recordings. The model suggests a mechanism whereby the hippocampus can control its own plasticity. These simulations demonstrate that the retrieval mechanism in several hippocampal models is feasible and that the theta rhythm and the cognitive evoked potentials may be generated by synaptic events modulating network parameters.

Cognition↗

PubMed2004

A Bayesian approach to reconstructing genetic regulatory networks with hidden factors.

MOTIVATION: We have used state-space models (SSMs) to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T cell activation. SSMs are a class of dynamic Bayesian networks in which the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be directly measured in a gene expression profiling experiment, for example: genes that have not been included in the microarray, levels of regulatory proteins, the effects of mRNA and protein degradation, etc. RESULTS: We have approached the problem of inferring the model structure of these state-space models using both classical and Bayesian methods. In our previous work, a bootstrap procedure was used to derive classical confidence intervals for parameters representing 'gene-gene' interactions over time. In this article, variational approximations are used to perform the analogous model selection task in the Bayesian context. Certain interactions are present in both the classical and the Bayesian analyses of these regulatory networks. The resulting models place JunB and JunD at the centre of the mechanisms that control apoptosis and proliferation. These mechanisms are key for clonal expansion and for controlling the long term behavior (e.g. programmed cell death) of these cells. AVAILABILITY: Supplementary data is available at http://public.kgi.edu/wild/index.htm and Matlab source code for variational Bayesian learning of SSMs is available at http://www.cse.ebuffalo.edu/faculty/mbeal/software.html.

Bayes Theorem↗

PubMed1995

Mapping of limbic seizure progressions utilizing the electrogenic status epilepticus model and the 14C-2-deoxyglucose method.

We have previously described a model of limbic status epilepticus in which chronic prolonged seizure states of immobile, exploratory, minor convulsive or clonic convulsive behavior are induced by intracerebral electrical stimulation; these states appear to belong to the same behavioral progression as kindled seizures. We postulated that the underlying seizure substrates, as mapped by the 14C-2-deoxyglucose method, should reflect a corresponding anatomic progression of discharge spread. Status epilepticus was induced in rat by pulsed-train current delivered for up to 90 min to one of several subcortical areas. Autoradiographs revealed that most of the observed patterns of seizure-induced metabolic activation comprised a hierarchical sequence, such that progressively more extensive patterns subsumed anatomic territories activated in less extensive patterns, thus allowing inferences as to the progression of discharge spread. In this sequence, the basolateral amygdala ipsilateral to the induction electrode was among the first structures to be activated. In successively larger activation patterns a small unilateral network related to basolateral amygdala was involved; this evolved through a transitional state to a unilateral extensive limbic pattern; which in turn was succeeded by bilateral extensive limbic activation. This hierarchical sequence culminated in a neocortical activation pattern, in which most of the forebrain was involved in intense seizure-induced activation. Seizure behaviors increased in severity in correspondence with the underlying seizure-activated anatomic substrate. In contrast, patterns of seizure activation were observed which did not fit within the early stages of the above sequence, although analysis indicates that the later stages of spread may be shared. The study of these patterns and those reported in the literature indicates that although limbic seizure networks may be anatomically distinct at their origination, further expansion is characterized by overlap; upon assumption of extensive patterns of activation the number of nuclei participating is so vast that the identity of the limbic originator is lost and common convulsive manifestations occur.

Amygdala↗

PubMed2006

HCNet: a database of heart and calcium functional network.

SUMMARY: The Heart and Calcium functional Network (HCNet) database is a collection of functional gene modules calculated from the microarray data compendium available from the GEO database. It is a specialized database designed to assist experimentalists for cardiac calcium signaling research by providing the pre-calculated gene clusters and their potential correlation network in heart. In the current release of HCNet, 57 functional modules from 786 target genes obtained by a bi-clustering analysis of 381 microarray datasets are available. Detailed information of the clusters such as expression profiles, network diagrams is provided in two categories, heart-specific genes and heart-specific genes along with calcium toolkit genes. Overrepresented gene ontological categories and transcription factors in each cluster are also provided to infer the biological implications of the detected functional modules. AVAILABILITY: HCNet is available at http://sbrg2.gist.ac.kr/hcnet.

Algorithms↗

PubMed2001

The potential use of SUISEKI as a protein interaction discovery tool.

Relevant information about protein interactions is stored in textual sources. This sources are commonly used not only as archives of what is already known but also as information for generating new knowledge, particularly to pose hypothesis about new possible interactions that can be inferred from the existing ones. This task is the more creative part of scientific work in experimental systems. We present a large-scale analysis for the prediction of new interactions based on the interaction network for the ones already known and detected automatically in the literature. During the last few years it has became clear that part of the information about protein interactions could be extracted with automatic tools, even if these tools are still far from perfect and key problems such as detection of protein names are not completely solved. We have developed a integrated automatic approach, called SUISEKI (System for Information Extraction on Interactions), able to extract protein interactions from collections of Medline abstracts. Previous experiments with the system have shown that it is able to extract almost 70% of the interactions present in relatively large text corpus, with an accuracy of approximately 80% (for the best defined interactions) that makes the system usable in real scenarios, both at the level of extraction of protein names and at the level of extracting interaction between them. With the analysis of the interaction map of Saccharomyces cerevisiae we show that interactions published in the years 2000/2001 frequently correspond to proteins or genes that were already very close in the interaction network deduced from the literature published before these years and that they are often connected to the same proteins. That is, discoveries are commonly done among highly connected entities. Some biologically relevant examples illustrate how interactions described in the year 2000 could have been proposed as reasonable working hypothesis with the information previously available in the automatically extracted network of interactions.

Cell Cycle↗

PubMedDate not supplied

The amphibian embryo: an experimental model for the in vivo analysis of interactions between embryonic cells and extracellular matrix molecules.

The early amphibian embryo provides an attractive model for the in vivo analysis of cell interactions with extracellular matrix components. During gastrulation, mesodermal cells use an anastomosing network of extracellular fibrils as substratum for their migration. These fibrils contain glycosaminoglycans and non collagenous proteins including laminin and fibronectin. The function of these extracellular components in the mesodermal cell migration process has been inferred from grafting experiments and microinjection of probes such as specific antibodies or GRGDS-containing peptides. Using the amphibian embryo as an experimental system, combination of microsurgical, cell behavioral and molecular approaches will provide new insights into cell-extracellular matrix interactions directing morphogenetic cell movements.

Amino Acid Sequence↗

PubMed2026

NLCD: A method to discover nonlinear causal relations among genes.

Distinguishing correlation from causation is a fundamental challenge in many scientific fields, including biology, especially when interventions like randomized controlled trials are infeasible and only observational data are available. Methods based on statistical tests of conditional independence within the Mendelian Randomization framework can detect causality between two observed variables that are each associated with a third instrumental variable. However, these methods for detecting causal relationships between traits (e.g., two gene expression or clinical traits associated with a genetic variant, all observed in the same population) often assume a linear relationship, thereby hindering the discovery of causal gene networks from genomics data. We have developed NLCD, a method for NonLinear Causal Discovery from genomics data based on nonlinear regression modeling and conditional feature importance scoring. NLCD uses these techniques to extend the statistical tests in an existing linear causal discovery method called the Causal Inference Test (CIT). We benchmarked NLCD against current state-of-the-art methods: CIT, Findr, and MRPC. On simulated datasets, NLCD performs comparably to most methods in detecting linear relations (Average AUPRC (Area Under the Precision-Recall Curve) of NLCD = 0.94, CIT = 0.94, Findr = 0.94, and MRPC = 0.99), and outperforms them in detecting nonlinear (sine and sawtooth type) relations between two genes (Average AUPRC of NLCD = 0.76, CIT = 0.60, Findr = 0.56, and MRPC = 0.73). When tested on a nonlinear subset of a yeast genomic dataset to recover known causal relations involving transcription factors, NLCD and CIT performed comparable to each other and slightly better than Findr and MRPC (Average AUPRC of NLCD = 0.82, CIT = 0.81, Findr = 0.71, and MRPC = 0.54). On application to a human genomic dataset, NLCD revealed active causal gene pairs (IRF1 → PSME1 and HLA-C → HLA-T) in the muscle tissue, and clarified the promises and challenges in discovering causal gene networks in tissues under in vivo human settings.

Humans↗

PubMed2006

Causal inference of regulator-target pairs by gene mapping of expression phenotypes.

BACKGROUND: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, then loci involved in regulatory control can theoretically be implicated. Recent efforts to construct gene regulatory networks from genotype and gene expression data have shown that biologically relevant networks can be achieved from an integrative approach. In this paper, we consider the problem of identifying individual pairs of genes in a direct or indirect, causal, trans-acting relationship. RESULTS: Inspired by epistatic models of multi-locus quantitative trait (QTL) mapping, we propose a unified model of expression and genotype to identify quantitative trait genes (QTG) by extending the conventional linear model to include both genotype and expression of regulator genes and their interactions. The model provides mapping of specific genes in contrast to standard linkage approaches that implicate large QTL intervals typically containing tens of genes. In simulations, we found that the method can often detect weak trans-acting regulators amid the background noise of thousands of traits and is robust to transcription models containing multiple regulator genes. We reanalyze several pleiotropic loci derived from a large set of yeast matings and identify a likely alternative regulator not previously published. However, we also found that many regulators can not be so easily mapped due to the presence of cis-acting QTLs on the regulators, which induce close linkage among small neighborhoods of genes. QTG mapped regulator-target pairs linked to ARN1 were combined to form a regulatory module, which we observed to be highly enriched in iron homeostasis related genes and contained several causally directed links that had not been identified in other automatic reconstructions of that regulatory module. Finally, we also confirm the surprising, previously published results that regulators controlling gene expression are not enriched for transcription factors, but we do show that our more precise mapping model reveals functional enrichment for several other biological processes related to the regulation of the cell. CONCLUSION: By incorporating interacting expression and genotype, our QTG mapping method can identify specific regulator genes in contrast to standard QTL interval mapping. We have shown that the method can recover biologically significant regulator-target pairs and the approach leads to a general framework for inducing a regulatory module network topology of directed and undirected edges that can be used to identify leads in pathway analysis.

Algorithms↗

PubMed2000

Learning in higher order Boltzmann machines using linear response.

We introduce an efficient method for learning and inference in higher order Boltzmann machines. The method is based on mean field theory with the linear response correction. We compute the correlations using the exact and the approximated method for a fully connected third order network of ten neurons. In addition, we compare the results of the exact and approximate learning algorithm. Finally we use the presented method to solve the shifter problem. We conclude that the linear response approximation gives good results as long as the couplings are not too large.

Artificial Intelligence↗

PubMed2003

Religious thought and behaviour as by-products of brain function.

Religious concepts activate various functionally distinct mental systems, present also in non-religious contexts, and 'tweak' the usual inferences of these systems. They deal with detection and representation of animacy and agency, social exchange, moral intuitions, precaution against natural hazards and understanding of misfortune. Each of these activates distinct neural resources or families of networks. What makes notions of supernatural agency intuitively plausible? This article reviews evidence suggesting that it is the joint, coordinated activation of these diverse systems, a supposition that opens up the prospect of a cognitive neuroscience of religious beliefs.

Journal Article↗

PubMed2000

Interfacial shear rheology of aged and heat-treated beta-lactoglobulin films: displacement by nonionic surfactant.

Interfacial shear rheology of adsorbed beta-lactoglobulin films (bulk protein concentration 10(-)(3) wt %) has been studied over the temperature range 20-90 degrees C using a two-dimensional Couette-type viscometer. Effects of the type of interface (air-water, triolein-water, and n-dodecane-water), the pH (2.0, 5.6, 6.0, 7.0, and 9.0), and the extent of the heat treatment have been assessed via measurements of changes in the apparent interfacial shear viscosity and elasticity before and after the addition of increasing amounts of nonionic surfactant Tween 20 (polyoxyethylene sorbitan monolaurate). The highest interfacial viscosities were obtained at the n-dodecane-water interface and the lowest at the air-water interface. Competitive displacement of protein from the interface by Tween 20 was easier at the air-water and n-dodecane-water interfaces as compared to the triolein-water interface. The surface shear viscosity was higher and the displacement by Tween 20 more difficult as the isoelectric point of the protein was approached, which is in agreement with the presence of a more strongly cross-linked protein network at the interface. The effect of heat treatment was dependent on the pH of the aqueous solution. No simple relationship between the surface rheological characteristics and the ease of displacement by Tween 20 could be inferred.

Hot Temperature↗

PubMed2004

Proteins associated with diseases show enhanced sequence correlation between charged residues.

MOTIVATION: Function of proteins or a network of interacting proteins often involves communication between residues that are well separated in sequence. The classic example is the participation of distant residues in allosteric regulation. Bioinformatic and structural analysis methods have been introduced to infer residues that are correlated. Recently, increasing attention has been paid to obtain the sequence properties that determine the tendency of disease-related proteins (Abeta peptides, prion proteins, transthyretin, etc.) to aggregate and form fibrils. Motivated in part by the need to identify sequence characteristics that indicate a tendency to aggregate, we introduce a general method that probes covariations in charged residues along the sequence in a given protein family. The method, which involves computing the sequence correlation entropy (SCE) using the quenched probability P(sk)(i,j) of finding a residue pair at a given sequence separation, sk, allows us to classify protein families in terms of their SCE. Our general approach may be a useful way in obtaining evolutionary covariations of amino acid residues on a genome wide level. RESULTS: We use a combination of SCE and clustering based on the principle component analysis to classify the protein families. From an analysis of 839 families, covering approximately 500,000 sequences, we find that proteins with relatively low values of SCE are predominantly associated with various diseases. In several families, residues that give rise to peaks in P(sk)(i,j) are clustered in the three-dimensional structure. For the class of proteins with low SCE values, there are significant numbers of mixed charged-hydrophobic (CH) and charged-polar (CP) runs. Our findings suggest that the low values of SCE and the presence of (CH) and/or (CP) may be indicative of disease association or tendency to aggregate. Our results led to the hypothesis that functions of proteins with similar SCE values may be linked. The hypothesis is validated with a few anecdotal examples. The present results also lead to the prediction that the overall charge correlations in proteins affect the kinetics of amyloid formation--a feature that is common to all proteins implicated in neurodegenerative diseases.

Algorithms↗

PubMed2005

Single nucleotide polymorphisms and haplotypes of CYP1A2 in a Japanese population.

In order to identify genetic polymorphisms and haplotype frequencies of CYP1A2 in a Japanese population, the enhancer and promoter regions, all the exons with their surrounding introns, and intron 1 were sequenced from genomic DNA from 250 Japanese subjects. Thirty-three polymorphisms were found, including 13 novel ones: 2 in the enhancer region, 5 in the exons, and 6 in the introns. The most common single nucleotide polymorphism (SNP) was -163C>A (CYP1A2*1F allele) with a 0.628 frequency. In addition to six previously reported non-synonymous SNPs, three novel ones, 125C>G (P42R, CYP1A2*15 allele, MPJ6_1A2032), 1130G>A (R377Q, *16 allele, MPJ6_1A2033), and 1367G>A (R456H, *8 allele, MPJ6_1A2019), were found with frequencies of 0.002, 0.002, and 0.004, respectively. No polymorphism was found in the known nuclear transcriptional factor-binding sites in the enhancer region. Based on linkage disequilibrium analysis, the CYP1A2 gene was analyzed as one haplotype block. Using the 33 detected polymorphisms, 14 haplotypes were unambiguously identified, and 17 haplotypes were inferred by aid of an expectation-maximization-based program. Among them, the second major haplotype CYP1A2*1L is composed of -3860G>A (*1C allele), -2467delT (*1D allele), and -163C>A (*1F allele). Network analysis suggested that relatively rare haplotypes were derived from three major haplotypes, *1A, *1M, and *1N in most cases. Our findings provide fundamental and useful information for genotyping CYP1A2 in the Japanese, and probably Asian populations.

Adrenergic beta-Antagonists↗

PubMed2006

[Centennial of the nobel prize for Golgi and Cajal--founding of modern neuroscience and irony of discovery].

In 1906, Golgi and Ramón y Cajal shared the Nobel Prize in Physiology or Medicine "in recognition of their work on the structure of the nervous system". However, it was an unusual occasion in the history of Nobel Prize award because their views on the structure of the nervous system were not only different but even opposite, creating the "storm center of histological controversy". Furthermore, the new staining method Cajal had employed to study the nervous system was developed by Golgi, creating an irony of discovery. In 1873, Golgi revolutionized the histological study of the nervous system by developing a new staining method, "la reazione nera" or black reaction, which allowed good visualization of axons, dendrites and glia. But because his stain was so selective, staining only about 3 percent of neurons, he was unable to see clearly how the neuronal processes ended as they approached other neurons. Consequently, he embraced the popular belief that neuronal processes physically fuse with each other--the "reticular theory". On the other hand, Cajal was incidentally introduced to the Golgi stain 14 years after its discovery and immediately realized its beauty. He found that better results could be produced by staining more intensely and cutting thicker sections. He further observed that the Golgi stain worked best on non-myelinated axons. The search for brains containing non-myelinated axons led him to study birds and very young mammals, including embryos. Cajal obtained fascinating results by modifying the Golgi stain and by studying avian and young mammalian brains. From those studies, Cajal was able to infer that axons and dendrites ended freely and did not physically anastomose. Therefore, he strongly advocated the "neuron theory". Golgi seemed to be too headstrong and too conservative to relinquish his belief that neurons constitute a network which reacts as a whole. On the other hand, Cajal's hard work using the Golgi stain led to new understanding on the structure and function of the nervous system, and earned him "the founder of modern neuroscience". This centennial occasion may be further impressed by Cajal's comment on the shared Nobel Prize that "what a cruel irony of fate of pair, like Siamese twins united by the shoulders, scientific adversaries of such contrasting character!".

History, 19th Century↗

PubMed2006

FCMAC-BYY: fuzzy CMAC using Bayesian Ying-Yang learning.

As an associative memory neural network model, the cerebellar model articulation controller (CMAC) has attractive properties of fast learning and simple computation, but its rigid structure makes it difficult to approximate certain functions. This research attempts to construct a novel neural fuzzy CMAC, in which Bayesian Ying-Yang (BYY) learning is introduced to determine the optimal fuzzy sets, and a truth-value restriction inference scheme is subsequently employed to derive the truth values of the rule weights of implication rules. The BYY is motivated from the famous Chinese ancient Ying-Yang philosophy: everything in the universe can be viewed as a product of a constant conflict between opposites-Ying and Yang, a perfect status is reached when Ying and Yang achieve harmony. The proposed fuzzy CMAC (FCMAC)-BYY enjoys the following advantages. First, it has a higher generalization ability because the fuzzy rule sets are systematically optimized by BYY; second, it reduces the memory requirement of the network by a significant degree as compared to the original CMAC; and third, it provides an intuitive fuzzy logic reasoning and has clear semantic meanings. The experimental results on some benchmark datasets show that the proposed FCMAC-BYY outperforms the existing representative techniques in the research literature.

Algorithms↗

PubMed2000

Sociality in the gray mouse lemur (Microcebus murinus) in northwestern Madagascar.

The mating system and social organization of the gray mouse lemur (Microcebus murinus) was investigated in two three-month field studies (covering a period before, during, and after the first mating season) in Ampijoroa, northwestern Madagascar. The spatial and temporal distribution of the sexes within a population was studied using mark/recapture techniques and radiotelemetry to assess possible contest or scramble competition between the males. Sociality was inferred from the occurrence and probability of nocturnal social encounters, the temporal stability of daily sleeping groups, and nocturnal ranging patterns of co-sleepers. Males and females were evenly distributed in the study area within a network of highly overlapping home ranges. No indications were found for the spatial monopolization of the females by certain dominant males. Males and females had spatial access to several potential mates; the mating system is therefore characterized as a multi-male/multi-female system. Male home range sizes increased during the first mating season, which was interpreted as an indicator for scramble competition between the males. Competitive mate searching, sperm competition, and temporary mate guarding as well as female mate choice are suggested as the most probable reproductive strategies. Over the course of the study the animals lived continually within the study area, and most females formed stable individualized sleeping associations. Females that slept together shared a higher percentage of their home range than did females that slept at different sites. It is suggested that this network of social relationships should be described as a dispersed but individualized neighborhood.

Animals↗

PubMed1986

Age-related morphological rearrangements of synaptic junctions in the rat cerebellum and hippocampus.

A quantitative investigation has been carried out on the age-related morphological changes of the synaptic junctions in the cerebellar glomeruli and in the supragranular layer of the hippocampal dentate gyrus of young (3 months), adult (12 months) and old (28-30 months) rats. The numerical (Nv) and surface (Sv) density as well as the average length (L) of E-PTA stained synapses was calculated by means of morphometric methods. The results we obtained showed a similar trend in both these areas of the CNS. Nv significantly increased between young and adult rats and significantly decreased in the old group, when compared both to young and adult animals. Sv appeared to be unchanged comparing young and adult animals, whereas it was significantly reduced in the old group. L showed a decrease between 3 and 12 months of age and appeared to be markedly increased in the old animals when compared to adult values. From the present findings it can be inferred that number (Nv) and size (L) of the synapses are in a close inverse relationship which, through the organism's life span, aims to maintain the constancy of the surface contact area (Sv) among the dendritic network. By considering Nv, L and Sv altogether per age group, we were able to obtain a reliable measurement of the morphological aspect of synaptic plasticity through different periods of the life. With regard to aging we found that, despite the 'compensative synaptogenesis' brought about by the increased size (L) of the synaptic appositions, the reactive capacity of old nerve cells is seriously impaired.

Age Factors↗

PubMed2026

Phosphoproteomic Profiling of Early-Stage Non-Small Cell Lung Cancer Provides Preliminary Evidence of Phosphorylation-Regulated Rho GTPase Signaling Driving Cytoskeletal Remodeling, Angiogenesis, and Cell Cycle Progression.

Non-small cell lung cancer (NSCLC) is the primary cause of cancer-related deaths worldwide. This can be attributed to the difficulty in early detection and the limited efficacy of available treatments, partly due to an incomplete understanding of the disease biology. Identification of key proteins involved in early-stage progression and understanding the underlying mechanisms can greatly contribute to the development of diagnostic and treatment strategies for NSCLC. Quantitative phosphoproteomic analysis was done on paired tumor tissues and adjacent normal lung tissues from early-stage NSCLC adenocarcinoma (LUAD) patients to allow for the identification of proteins with differential phosphorylation and their associated pathways. A total of 6483 phosphoproteins were identified, with 1229 proteins having significantly higher phosphorylation and 701 proteins having significantly lower phosphorylation in the tumor tissues. All MS data were deposited in ProteomeXchange with the identifier PXD071583. Function enrichment analysis showed that the differentially phosphorylated proteins and phosphosites were primarily involved in Rho GTPase signaling and cytoskeleton remodeling. Analysis of protein interaction networks suggests that the predicted kinase activity likely drives malignant transformation in NSCLC LUAD, presumably through Rho GTPase-mediated angiogenesis and cell cycle progression. More importantly, this study identified several protein phosphosites with differential phosphorylation and inferred kinase-phosphosite activities that have not previously been reported in NSCLC LUAD.

Humans↗