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PubMed2003

Sequential Bayesian decoding with a population of neurons.

Population coding is a simplified model of distributed information processing in the brain. This study investigates the performance and implementation of a sequential Bayesian decoding (SBD) paradigm in the framework of population coding. In the first step of decoding, when no prior knowledge is available, maximum likelihood inference is used; the result forms the prior knowledge of stimulus for the second step of decoding. Estimates are propagated sequentially to apply maximum a posteriori (MAP) decoding in which prior knowledge for any step is taken from estimates from the previous step. Not only do we analyze the performance of SBD, obtaining the optimal form of prior knowledge that achieves the best estimation result, but we also investigate its possible biological realization, in the sense that all operations are performed by the dynamics of a recurrent network. In order to achieve MAP, a crucial point is to identify a mechanism that propagates prior knowledge. We find that this could be achieved by short-term adaptation of network weights according to the Hebbian learning rule. Simulation results on both constant and time-varying stimulus support the analysis.

Bayes Theorem↗

PubMed1994

Mixed Bayesian networks: a mixture of Gaussian distributions.

Mixed Bayesian networks are probabilistic models associated with a graphical representation, where the graph is directed and the random variables are discrete or continuous. We propose a comprehensive method for estimating the density functions of continuous variables, using a graph structure and a set of samples. The principle of the method is to learn the shape of densities from a sample of continuous variables. The densities are approximated by a mixture of Gaussian distributions. The estimation algorithm is a stochastic version of the Expectation Maximization algorithm (Stochastic EM algorithm). The inference algorithm corresponding to our model is a variant of junction three method, adapted to our specific case. The approach is illustrated by a simulated example from the domain of pharmacokinetics. Tests show that the true distributions seem sufficiently fitted for practical application.

Algorithms↗

PubMed2026

Dissecting spatial patterning and signaling with directional diffusion in spatial multi-omics.

Spatial multi-omics sequencing enables the simultaneous profiling of transcriptomics, proteomics, and epigenomics at a spatial resolution, offering insights into complex tissue organization and molecular regulation. However, the effective integration of multiple omics modalities in a spatial context remains a major challenge. Here, we present SpaDDM, a spatial multi-omics integration framework based on directional diffusion models (DDMs), which supports spatial pattern identification, cross-omics alignment, and inter-and intracellular signaling flow analysis. SpaDDM employs DDM-based graph networks to learn omics-specific representations by jointly incorporating spatial coordinates and molecular measurements within each modality, followed by an attention mechanism to align features across modalities. We benchmarked SpaDDM on diverse spatial multi-omics datasets, including transcriptomics-epigenomics and transcriptomics-proteomics combinations across multiple tissues and species. SpaDDM consistently outperformed existing methods by more accurately deciphering spatial tissue patterns and effectively reducing the boundary noise between spatial regions. Moreover, the learned low-dimensional coembedded representations of individual cells serve as integral mediators for inferring the signaling flows that underlie spatial patterning. Finally, we demonstrated that SpaDDM alignment of complementary information across multi-omics layers facilitates cross-omics translation and significantly improves the prediction of cell state alignments.

Multiomics↗

PubMed2006

Use of gene expression profiling to identify a novel glucocorticoid sensitivity determining gene, BMPRII.

Wide variation in glucocorticoid (Gc) sensitivity exists between individuals which may influence susceptibility to, and treatment response of, inflammatory diseases. To determine a genetic fingerprint of Gc sensitivity 100 healthy human volunteers were polarized into the 10% most Gc-sensitive and 10% most Gc-resistant following a low dose dexamethasone (0.25 mg) suppression test. Gene expression profiling of primary lymphocytes identified the 98 most significantly Gc regulated genes. These genes were used to build a subnetwork of Gc signaling, with 54 genes mapping as nodes, and 6 non-Gc regulated genes inferred as signaling nodes. Twenty four of the 98 genes showed a difference in Gc response in vitro dependent on the Gc sensitivity of their donor individuals in vivo. A predictive model was built using both partial least squares discriminate analysis and support vector machines that predicted donor glucocorticoid sensitivity with 87% accuracy. Discriminating genes included bone morphogenetic protein receptor, type II (BMPRII). Transfection studies showed that BMPRII modulated Gc action. These studies reveal a broad base of gene expression that predicts Gc sensitivity and determine a Gc signaling network in human primary T lymphocytes. Furthermore, this combined gene profiling, and functional analysis approach has identified BMPRII as a modulator of Gc signaling.

Adult↗

PubMedDate not supplied

A global experimental system approach of karst springs' hydrographs and chemographs.

Investigation techniques for karst flow systems are based mainly on the study of different signals leaving the system caused by natural or induced external influences. Each signal represents one of the systems outputs (e.g., hydraulic, chemical, physical, or isotopic responses) that reflect the characteristics of the entire system. In this paper, we present a method to infer information about the structure of karst systems. It is based on a simultaneous analysis of chemical and hydraulic responses. Beside the classical piston flow at the beginning of a flood pulse, we define a chemically based recession flow phase. During this phase, field data show that the concentration of total dissolved solids can be considered as an exponential function of the logarithm of flow. This relationship allows two parameters to be defined, one of which is dependent on the structure and degree of development of the karst conduit network, the other is dependent mainly on bioclimatic factors. Data collected from seven karst springs are used to support ideas introduced in the paper.

Climate↗

PubMed2002

A 3-D structural model of solid self-assembled chlorophyll a/H(2)O from multispin labeling and MAS NMR 2-D dipolar correlation spectroscopy in high magnetic field.

Magic angle spinning (MAS) NMR with Lee-Goldburg cross-polarization (LG-CP) is used to promote long-range heteronuclear transfer of magnetization and to constrain a structural model for uniformly labeled chlorophyll a/H(2)O. An effective maximum transfer range d(max) can be determined experimentally from the detection of a gradually decreasing series of intramolecular correlations with the (13)C along the molecular skeleton. To probe intermolecular contacts, d(max) can be set to approximately 4.2 A by choosing an LG-CP contact time of 2 ms. Long-range (1)H-(13)C correlations are used in conjunction with carbon and proton aggregation shifts to establish the stacking of the chlorophyll a (Chl a) molecules. First, high-field (14.1 T) 2-D MAS NMR homonuclear ((13)C-(13)C) dipolar correlation spectra provide a complete assignment of the carbon chemical shifts. Second, proton chemical shifts are obtained from (1)H-(13)C heteronuclear dipolar correlation spectroscopy in high magnetic field. The shift constraints and long-range (1)H-(13)C intermolecular correlations reveal a 2-D stacking homologous to the molecular arrangement in crystalline solid ethyl-chlorophyllide a. A doubling of a small subset of the carbon resonances, in the 7-methyl region of the molecule, provides evidence for two marginally different well-defined molecular environments. Evidence is found for the presence of neutral structural water molecules forming a hydrogen-bonded network to stabilize Chl a sheets. In line with the microcrystalline order observed for the rings, the long T(1)'s, and absence of conformational shifts for the (13)C in the phytyl tails, it is proposed that the Chl a form a rigid 3-D space-filling structure. Probably the only way this can be realized with the sheets is by forming bilayers with interpenetration of elongated tails. Such a 3-D space-filling organization of the aggregated Chl a from MAS NMR would match existing models inferred from electron microscopy and low-resolution X-ray powder diffraction, while a micellar model based on neutron diffraction and antiparallel stacking observed in solution can be discarded.

Carbon Isotopes↗

PubMed2006

Base damage and single-strand break repair: mechanisms and functional significance of short- and long-patch repair subpathways.

A large variety of DNA lesions induced by environmental agents or arising as an outcome of cellular metabolism are counteracted by a complex network of proteins that belong to the base excision repair/single strand break repair (BER/SSBR) processes. No matter whether the initial lesions are modified DNA bases or single-strand breaks with non-conventional termini these processes are completed either by replacement of a single (short-patch, SP) or more (long-patch, LP) nucleotides by different arrays of proteins. Here, the factors that are involved in the selection between SP- and LP-BER/SSBR are reviewed. The biological significance of these alternative subpathways is also presented as inferred from mutant mouse/cell models.

Animals↗

PubMed2001

Sorption of phenanthrene by reference smectites.

Fate and behavior of nonionic hydrophobic organic compounds (HOCs) in the environment is mainly controlled by their interactions with various components of soils and sediments. Due to their large surface area and abundance in many soils, smectites may greatly influence the fate and transport of HOCs in the environment. We used phenanthrene as a probe to explore the potential of reference smectites to sorb HOCs from aqueous solution. Batch experiments were used to construct phenanthrene sorption isotherms, and possible sorption mechanisms were inferred from the shape of the isotherms. Our results demonstrate that smectites can retain large amounts of phenanthrene from water. Phenanthrene sorption capacities of the reference smectites investigated in this study were comparable to those of soil clays containing a considerable amount of organic matter. Hectorite exhibited the highest sorption affinity and capacity followed by Panther Creek montmorillonite. The lack of correlation between Freundlich sorption constants (K'f) and indices of charge or hydrophobicity suggests that sorption of phenanthrene by smectites is primarily a physical phenomenon. Capillary condensation into a network of nanoor micropores created by quasicrystals is likely to be a dominant mechanism of phenanthrene retention by smectites.

Adsorption↗

PubMed2004

BACUS: A Bayesian protocol for the identification of protein NOESY spectra via unassigned spin systems.

NMR frequency assignments are usually considered a prerequisite for the analysis of NOESY spectra, in turn required for the calculation of biomolecular structures. In contrast, as we propose here, relatively high numbers of unambiguous NOE identities can be consistently achieved in an automated manner by relying only on grouping resonances into connected spin systems. To achieve this goal, we have developed for proteins two protocols, SPI and BACUS, based on Bayesian inference. SPI (Grishaev and Llinás, 2002c) produces a list of the (1)H resonance frequencies from homo- and hetero-nuclear multidimensional spectra, grouped into effective spin systems. BACUS automatically establishes probabilistic identities of NOESY cross-peaks in terms of the chemical shifts provided by SPI. BACUS requires neither assignment of resonances nor an initial structural model. It successfully copes with chemical shift overlap and does so without cycling through 3D structure calculations. The method exploits the self-consistency of the NOESY graph by taking advantage of a network of J- as well as NOE-connected "reporter" protons sorted via SPI. BACUS was validated by tests on experimental NOESY data recorded for the col 2 and kringle 2 domains.

Bayes Theorem↗

PubMed1992

Respiratory-related neural assemblies in the brain stem midline.

1. The initial objective of this study was to determine whether respiratory-related neural assemblies exist in the brain stem midline. A second goal was to seek evidence for concurrent relationships among the neurons that could generate the detected synchrony. 2. Experiments were conducted on anesthetized, paralyzed, bilaterally vagotomized, artificially ventilated cats. Spike trains of four to nine simultaneously monitored neurons were recorded in the regions of n. raphe obscurus-n. raphe pallidus and n. raphe magnus. 3. Data were analyzed with cycle-triggered histograms, cross-correlograms, snowflakes, and the gravitational representation. A significance test for the gravity method was developed and tested with spike trains generated by simulated networks with defined connections. 4. Ninety-three groups of neurons from 24 cats were studied. Thirty-nine groups from 19 cats included neurons that discharged synchronously on a millisecond time scale; less than or equal to 19 pairs of synchronously discharging neurons were found in one group. Twenty-seven of these 39 groups included neurons that had respiratory-modulated firing rates and discharged synchronously with other group members. Synchronous assemblies included cells monitored at rostral or caudal locations, or both. 5. Six classes of relationships were inferred from groups of neurons with multiple correlations: divergence (n = 11); convergence (n = 7); connections with opposite actions between neurons (n = 5); projections of synchronous neurons to separate targets (n = 5); projections to one neuron in a synchronous group (n = 4); and projections between two synchronous groups with common elements (n = 6). 6. The results document the existence of assemblies of synchronously discharging respiratory-related neurons in midline regions of the brain stem and suggest that divergent excitatory and inhibitory connections within the midline participate in the generation of that synchrony. Links between assemblies may operate to stabilize their collective activity in a particular state.

Afferent Pathways↗

PubMed1999

Response time distributions: some simple effects of factors selectively influencing mental processes.

When hypotheses about mental processing are tested with response times, inferences are often based on means, and occasionally on variance or skewness. Calculations on entire distributions of response times are more informative and can be conveniently carried out. Recently investigators have been updating procedures primarily based on means (such as additive factors tests) to procedures employing entire distribution functions. In one such advance, Nozawa and Townsend upgraded earlier tests of whether factors selectively influence serial or parallel processes, and whether parallel processes enter AND gates or OR gates. We discuss generalizations of the tests to complex arrangements of processes in networks. Results for a particularly difficult network, the Wheatstone bridge, are presented here. We use simulations to demonstrate the feasibility of the tests, and the possibility of mimicking.

Humans↗

PubMed1995

Assessing the behavioral impact of a diagnostic decision support system.

This paper describes a prototype for research to evaluate the impact of diagnostic decision support systems on the behavior of physicians. Several indices that can be used to quantify the magnitude of impact are proposed. A large medical diagnostic knowledge base in internal medicine (the Iliad knowledge base) was used in this evaluation. The impact on behavior when different inference models are run against this knowledge base is evaluated for two different case domains and physician's specialties.

Analysis of Variance↗

PubMed2026

Integrative methylation and miRNA dysregulation in dlPFC reveal distinct molecular signatures of suicide and non-suicide subtypes in major depressive disorder.

AIM: Major depressive disorder (MDD) is a leading cause of disability and carries a high risk of suicide. MicroRNAs (miRNAs) are epigenetic regulators implicated in MDD and can be regulated by DNA methylation, potentially reshaping downstream gene networks. We investigated methylation-linked miRNA dysregulation and explored whether these changes are specifically associated with suicide among MDD patients. METHODS: Genome-wide DNA methylation profiling of the dorsolateral prefrontal cortex from 15 MDD patients who died by suicide (MDD+S), 17 MDD patients who died from causes other than suicide (MDD-S), and 16 controls (C) using the Illumina 850K MethylationEPIC array was integrated with small RNA sequencing-based miRNA quantification to identify miRNA-associated differentially methylated probes (DMPs), link methylation to miRNA expression, and infer downstream targets and pathways. RESULTS: Differential methylation analysis (P ≤ 0.05) revealed 139 miRNA-linked DMPs in C vs. MDD+/-S, 135 in C vs. MDD-S, 179 in C vs. MDD+S, and the highest in MDD+S vs. MDD-S (235). CpG-miRNA pairing (within 1500kb promoter) followed by Spearman correlation identified inverse associations between CpG β values and miRNA expression, with the most consistent signals in suicide-status-stratified subsets, including cg06341821-hsa-miR-574-3p and cg25451306-hsa-miR-2110 in MDD+S-related contrasts, and cg06179179-hsa-miR-595 in MDD-S-related contrasts. High-confidence target prediction and ClueGO enrichment indicated distinct biology: miR-595 target genes in MDD-S were enriched for interferon/innate immune signaling, whereas miR-2110 target genes in MDD+S were enriched for ligand-gated ion channel activity and synaptic/receptor signaling. CONCLUSION: This integrated approach identifies methylation-regulated miRNA pathways that may play key roles in the molecular pathogenesis of MDD and suicide.

Humans↗

PubMedDate not supplied

[Analysis and cognitive modelling of the analogical process in psychosis].

The disturbances of cognitive processes in psychotic patients are well known: the delusional interpretation is "the inference from a right perception into a wrong concept" (Dromard), "an wrong intuition about the meaning of what is perceived, seen or heard" (H. Ey). Analogy is the very core of any cognitive process: relating a strange thing to some object already part of the experience enables to set up differences, oppositions, connections, classes. Any semantic process (something stands for another thing) originates in analogy. It is the basis of every interpretation and world's knowledge. Its soundness is by no means reliable, but for the inner strength of the analogical network and its power to integrate new objects. It's easy to fall out of the track... A wrong analogy, better, a wrong one that would not be acknowledged as a mistake, would be enough: the gap is quite narrow between interpretations leading either to understanding or to misreading, only filled through the relation of other people providing the necessary clues. The contemporary papers about cognitive process are driving towards two main trends: 1) Neuromimetic models, and the building of neuronal networks, whose emergent properties point out the basically analogical character of representations, learning and memory. 2) Cognitive models, dealing with representations and algorithms, and leading to Artificial Intelligence Programs. We tried to build a model (both cognitive and AI) of the analogical process and its psychotic disturbances. Our model describes how simple analogical problems are solved: If (A) becomes (B), what about (C)? Making up the psychological model and its AI translation led to propound the concept of Universes as sets consisting of ONE likely or relevant link between two objects, and such intrinsic of extrinsic properties of the objects as are involved in this relation. The model uses 3 different universes: Universe U1, made up of one of the possible transformation kinks from (A) to (B) and (A)'s properties involved in this actual transformation. Universe U2, made out of the likeness link between Universe U1 and (C). Universe U3, performing in fact the validation procedure of the result. The analogical reasoning goes through the three universes, along an iterative loop again and again until a nice result is found.(ABSTRACT TRUNCATED AT 400 WORDS)

Artificial Intelligence↗

PubMed2006

Diffuse and point sources of silica in the Seine River watershed.

Dissolved silica (DSi) is believed to enter aquatic ecosystems primarily through diffuse sources by weathering. Point sources have generally been considered negligible, although recent reports of DSi inputs from domestic and industrial sources suggest otherwise. In addition, particulate amorphous silica (ASi) inputs from terrestrial ecosystems during soil erosion and in vegetation can dissolve and also be a significant source of DSi. We quantify here both point and diffuse sources of DSi and particulate ASi to the Seine River watershed. The total per capita point source inputs of Si (DSi + ASi) were found to be 1.0 and 0.8 g Si inhabitant(-1) d(-1) in raw and treated waters of the Achères wastewater treatment plant, in agreement with calculations based on average food intake and silica-containing washing products consumption. A mass balance of Si inputs and outputs for the Seine drainage network was established for wet and dry hydrological conditions (2001 and 2003, respectively). Diffuse sources of Si are of 1775 kg Si km(-2) y(-1) in wet conditions and 762 kg Si km(-2) y(-1) in dry conditions, with the proportion of ASi around 6%. Point sources of Si from urban discharge can contribute to more than 8% of the total Si inputs at the basin scale in hydrologically dry years. An in-stream retention of 6% of total inputs in dry conditions and 12% in wet conditions is inferred from the budget.

Ecosystem↗

PubMed2005

Identifying active transcription factors and kinases from expression data using pathway queries.

MOTIVATION: Although progress has been made identifying regulatory relationships from expression data in general, only few methods have focused on detecting biological mechanisms like active pathways using a single measurement. This is of particular importance when only few measurements are available, e.g. if special cell types or conditions are under investigation. Here we present a method to test user specified hypotheses (pathway queries) on expression data where prior knowledge is given in the form of networks and functional annotations. Based on this method, we develop a scoring function to identify active transcription factors or kinases, thus making a first step toward explaining the measured expression data. RESULTS: We apply the algorithm to the Rosetta Yeast Compendium dataset, finding that in many cases the results are in concordance with biological knowledge. We were able to confirm that transcription factors and to a lesser degree, kinases identified by our method play an important role in the biological processes affected by the respective knockouts. Furthermore, we show that correlation of inferred activities can provide evidence for a physical interaction or cooperation of transcription factors where correlation of plain expression data fails to do so.

Algorithms↗

PubMed1999

Development, evolution, and corroboration.

The cloning of genes involved in pathways fundamental to morphogenesis has opened the door to visualizing expression of developmental regulatory genes in many organisms. Expression data have become technical commonplace in analysis of mutants of Drosophila melanogaster and a handful of other genetic model systems. Many researchers have used probes and extended the logic from studies of D. melanogaster for comparisons of expression patterns to infer developmental bases for homologous structures among animals with diverse body plans. This research program has led to exciting but sweeping generalizations about how development evolves. Here we examine several underlying assumptions of this approach in terms of comparative and historical biology. First, we evaluate the logic that underlies the equation of gene expression similarity with homologous morphology. Second, we examine epistemological issues surrounding the descriptive visualization of gene expression patterns. We conclude by examining the role of phylogenetic coding and mapping of these patterns to examine the evolution of complex gene regulatory networks.

Animals↗

PubMed2006

Comparative genomics and protein domain graph analyses link ubiquitination and RNA metabolism.

The human gene parkin, known to cause familial Parkinson disease, as well as several other genes, likely involved in other neurodegenerative diseases or in cancer, encode proteins of the RBR family of ubiquitin ligases. Here, we describe the structural diversity of the RBR family in order to infer their functional roles. Of particular interest is a relationship detected between RBR-mediated ubiquitination and RNA metabolism: a few RBR proteins contain RNA binding domains and DEAH-box RNA helicase domains. Global protein domain graph analyses demonstrate that this connection is not RBR-specific, but instead many other proteins contain both ubiquitination and RNA-related domains. These proteins are present in animals, plants and fungi, suggesting that the link between these two cellular processes is ancient. Our results show that global bioinformatic approaches, involving comparative genomics and domain network analyses, may unearth novel functional relationships involving well-known and thoroughly studied groups of proteins.

Algorithms↗