Exact mean field inference in asymmetric kinetic Ising systems

We develop an elementary mean field approach for fully asymmetric kinetic Ising models, which can be applied to a single instance of the problem. In the case of the asymmetric SK model this method gives the exact values of the local magnetizations and the exact relation between equal-time and time-delayed correlations. It can also be used to solve efficiently the inverse problem, i.e. determine the couplings and local fields from a set of patterns, also in cases where the fields and couplings are time-dependent. This approach generalizes some recent attempts to solve this dynamical inference problem, which were valid in the limit of weak coupling. It provides the exact solution to the problem also in strongly coupled problems. This mean field inference can also be used as an efficient approximate method to infer the couplings and fields in problems which are not infinite range, for instance in diluted asymmetric spin glasses.Comment: 10 pages, 7 figure

First-principles investigation of spin polarized conductance in atomic carbon wire

We analyze spin-dependent energetics and conductance for one dimensional (1D) atomic carbon wires consisting of terminal magnetic (Co) and interior nonmagnetic (C) atoms sandwiched between gold electrodes, obtained employing first-principles gradient corrected density functional theory and Landauer's formalism for conductance. Wires containing an even number of interior carbon atoms are found to be acetylenic with sigma-pi bonding patterns, while cumulene structures are seen in wires containing odd number of interior carbon atoms, as a result of strong pi-conjugation. Ground states of carbon wires containing up to 13 C atoms are found to have anti-parallel spin configurations of the two terminal Co atoms, while the 14 C wire has a parallel Co spin configuration in the ground state. The stability of the anti-ferromagnetic state in the wires is ascribed to a super-exchange effect. For the cumulenic wires this effect is constant for all wire lengths. For the acetylenic wires, the super-exchange effect diminishes as the wire length increases, going to zero for the atomic wire containing 14 carbon atoms. Conductance calculations at the zero bias limit show spin-valve behavior, with the parallel Co spin configuration state giving higher conductance than the corresponding anti-parallel state, and a non-monotonic variation of conductance with the length of the wires for both spin configurations.Comment: revtex, 6 pages, 5 figure

Origin of Corrections to Mean-field at the Onset of Unjamming

We present a detailed analysis of the unjamming transition in 2D frictionless disk packings using a static correlation function that has been widely used to study disordered systems. We show that this point-to-set (PTS) correlation function exhibits a dominant length scale that diverges as the unjamming transition is approached through decompression. In addition, we identify deviations from meanfield predictions, and present detailed analysis of the origin of non-meanfield behavior. A mean-field bulk-surface argument is reviewed. Corrections to this argument are identified, which lead to a change in the functional form of the critical PTS boundary size. An entropic description of the origin of the correlations is presented, and simple rigidity assumptions are shown to predict the functional form of the critical PTS boundary size as a function of the pressure

Receptor Conformations Involved in Dopamine D2L Receptor Functional Selectivity Induced by Selected Transmembrane-5 Serine Mutations

Although functional selectivity is now widely accepted, the molecular basis is poorly understood. We have studied how aspects of transmembrane region 5 (TM5) of the dopamine D2L receptor interacts with three rationally selected rigid ligands (dihydrexidine, dinapsoline, and dinoxyline) and the reference compounds dopamine and quinpirole. As was expected from homology modeling, mutation of three TM5 serine residues to alanine (S5.42A, S5.43A, S5.46A) had little effect on antagonist affinity. All three mutations decreased the affinity of the agonist ligands to different degrees, S5.46A being somewhat less affected. Four functions [adenylate cyclase (AC), extracellular signal-regulated kinase 1/2 phosphorylation (MAPK), arachidonic acid release (AA), and guanosine 5′-O-(3-thio)triphosphate binding (GTPγS)] were assessed. The intrinsic activity (IA) of quinpirole was unaffected by any of the mutations, whereas S5.42A and S5.46A mutations abolished the activity of dopamine and the three rigid ligands, although dihydrexidine retained IA at MAPK function only with S5.42A. Remarkably, S5.43A did not markedly affect IA for AC and MAPK for any of the ligands and eliminated AA activity for dinapsoline and dihydrexidine but not dinoxyline. These data suggest that this mutation did not disrupt the overall conformation or signaling ability of the mutant receptors but differentially affected ligand activation. Computational studies indicate that these D2 agonists stabilize multiple receptor conformations. This has led to models showing the stabilized conformations and interhelical and receptor-ligand contacts corresponding to the different activation pathways stabilized by various agonists. These data provide a basis for understanding D2L functional selectivity and rationally discovering functionally selective D2 drugs

DistiLD Database: diseases and traits in linkage disequilibrium blocks

Genome-wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with the risk of hundreds of diseases. However, there is currently no database that enables non-specialists to answer the following simple questions: which SNPs associated with diseases are in linkage disequilibrium (LD) with a gene of interest? Which chromosomal regions have been associated with a given disease, and which are the potentially causal genes in each region? To answer these questions, we use data from the HapMap Project to partition each chromosome into so-called LD blocks, so that SNPs in LD with each other are preferentially in the same block, whereas SNPs not in LD are in different blocks. By projecting SNPs and genes onto LD blocks, the DistiLD database aims to increase usage of existing GWAS results by making it easy to query and visualize disease-associated SNPs and genes in their chromosomal context. The database is available at http://distild.jensenlab.org/

Varietas: a functional variation database portal

Current high-throughput technologies for investigating genomic variation in large population based samples produce data on a scale of millions of variations. Browsing through these results and identifying relevant functional variations is a major hurdle in these genome-wide association studies. In order to help researchers locate the most promising associations, we have developed a web-based database portal called Varietas. Varietas can be used for retrieving information concerning genomic variations such as single-nucleotide polymorphisms (SNPs), copy number variants and insertions/deletions, while enabling users to annotate large number of variations in a batch like manner and to find information about related genes, phenotypes and diseases. Varietas also links out to various external genomic databases, allowing users to quickly browse through a set of variations and follow the most promising leads. Varietas periodically integrates data from the major SNP and genome databases, including Ensembl genome database, NCBI dbSNP database, The Genomic Association Database and SNPedia

Quantifying single nucleotide variant detection sensitivity in exome sequencing

BACKGROUND: The targeted capture and sequencing of genomic regions has rapidly demonstrated its utility in genetic studies. Inherent in this technology is considerable heterogeneity of target coverage and this is expected to systematically impact our sensitivity to detect genuine polymorphisms. To fully interpret the polymorphisms identified in a genetic study it is often essential to both detect polymorphisms and to understand where and with what probability real polymorphisms may have been missed. RESULTS: Using down-sampling of 30 deeply sequenced exomes and a set of gold-standard single nucleotide variant (SNV) genotype calls for each sample, we developed an empirical model relating the read depth at a polymorphic site to the probability of calling the correct genotype at that site. We find that measured sensitivity in SNV detection is substantially worse than that predicted from the naive expectation of sampling from a binomial. This calibrated model allows us to produce single nucleotide resolution SNV sensitivity estimates which can be merged to give summary sensitivity measures for any arbitrary partition of the target sequences (nucleotide, exon, gene, pathway, exome). These metrics are directly comparable between platforms and can be combined between samples to give “power estimates” for an entire study. We estimate a local read depth of 13X is required to detect the alleles and genotype of a heterozygous SNV 95% of the time, but only 3X for a homozygous SNV. At a mean on-target read depth of 20X, commonly used for rare disease exome sequencing studies, we predict 5–15% of heterozygous and 1–4% of homozygous SNVs in the targeted regions will be missed. CONCLUSIONS: Non-reference alleles in the heterozygote state have a high chance of being missed when commonly applied read coverage thresholds are used despite the widely held assumption that there is good polymorphism detection at these coverage levels. Such alleles are likely to be of functional importance in population based studies of rare diseases, somatic mutations in cancer and explaining the “missing heritability” of quantitative traits

The pattern of gray matter atrophy in Parkinson’s disease differs in cortical and subcortical regions

Cortical and subcortical gray matter (GM) atrophy may progress differently during the course of Parkinson's disease (PD). We delineated and compared the longitudinal pattern of these PD-related changes

PolymiRTS Database 2.0: linking polymorphisms in microRNA target sites with human diseases and complex traits

The polymorphism in microRNA target site (PolymiRTS) database aims to identify single-nucleotide polymorphisms (SNPs) that affect miRNA targeting in human and mouse. These polymorphisms can disrupt the regulation of gene expression by miRNAs and are candidate genetic variants responsible for transcriptional and phenotypic variation. The database is therefore organized to provide links between SNPs in miRNA target sites, cis-acting expression quantitative trait loci (eQTLs), and the results of genome-wide association studies (GWAS) of human diseases. Here, we describe new features that have been integrated in the PolymiRTS database, including: (i) polymiRTSs in genes associated with human diseases and traits in GWAS, (ii) polymorphisms in target sites that have been supported by a variety of experimental methods and (iii) polymorphisms in miRNA seed regions. A large number of newly identified microRNAs and SNPs, recently published mouse phenotypes, and human and mouse eQTLs have also been integrated into the database. The PolymiRTS database is available at http://compbio.uthsc.edu/miRSNP/