Transcription Factor-DNA Binding Via Machine Learning Ensembles

We present ensemble methods in a machine learning (ML) framework combining predictions from five known motif/binding site exploration algorithms. For a given TF the ensemble starts with position weight matrices (PWM's) for the motif, collected from the component algorithms. Using dimension reduction, we identify significant PWM-based subspaces for analysis. Within each subspace a machine classifier is built for identifying the TF's gene (promoter) targets (Problem 1). These PWM-based subspaces form an ML-based sequence analysis tool. Problem 2 (finding binding motifs) is solved by agglomerating k-mer (string) feature PWM-based subspaces that stand out in identifying gene targets. We approach Problem 3 (binding sites) with a novel machine learning approach that uses promoter string features and ML importance scores in a classification algorithm locating binding sites across the genome. For target gene identification this method improves performance (measured by the F1 score) by about 10 percentage points over the (a) motif scanning method and (b) the coexpression-based association method. Top motif outperformed 5 component algorithms as well as two other common algorithms (BEST and DEME). For identifying individual binding sites on a benchmark cross species database (Tompa et al., 2005) we match the best performer without much human intervention. It also improved the performance on mammalian TFs. The ensemble can integrate orthogonal information from different weak learners (potentially using entirely different types of features) into a machine learner that can perform consistently better for more TFs. The TF gene target identification component (problem 1 above) is useful in constructing a transcriptional regulatory network from known TF-target associations. The ensemble is easily extendable to include more tools as well as future PWM-based information.Comment: 33 page

Wake Vortex Inverse Model User's Guide

NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input file, with preferred parameters values, is given in Appendix A. An example of the plot generated at a normal completion of the inversion is shown in Appendix B

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.This work was supported by the National Institutes of Health, R01GM103502-05 to CD, ZH and DS. Partial support was also provided by grants from the Office of Science (BER), U.S. Department of Energy (DE-SC0004962), the Joslin Diabetes Center (Pilot & Feasibility grant P30 DK036836), the Army Research Office under MURI award W911NF-12-1-0390, National Institutes of Health (1RC2GM092602-01, R01GM089978 and 5R01DE024468), NSF (1457695), and Defense Advanced Research Projects Agency Biological Technologies Office (BTO), Program: Biological Robustness In Complex Settings (BRICS), Purchase Request No. HR0011515303, Program Code: TRS-0 Issued by DARPA/CMO under Contract No. HR0011-15-C-0091. Funding for open access charge: National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. (R01GM103502-05 - National Institutes of Health; 1RC2GM092602-01 - National Institutes of Health; R01GM089978 - National Institutes of Health; 5R01DE024468 - National Institutes of Health; DE-SC0004962 - Office of Science (BER), U.S. Department of Energy; P30 DK036836 - Joslin Diabetes Center; W911NF-12-1-0390 - Army Research Office under MURI; 1457695 - NSF; HR0011515303 - Defense Advanced Research Projects Agency Biological Technologies Office (BTO), Program: Biological Robustness In Complex Settings (BRICS); HR0011-15-C-0091 - DARPA/CMO; National Institutes of Health)Published versio

Handgun carrying among youth in the United States

Despite a wealth of research finding that adolescents who carry handguns are involved in risky behaviors, there has been little exploration into the heterogeneity of this behavior. Using a pooled sample of 12- to 17-year-olds from the National Study on Drug Use and Health who report past-year handgun carrying (N = 7,872), this study identified four subgroups of handgun carriers: low risk (n = 3,831; 47.93%), alcohol and marijuana users (n = 1,591; 20.16%), fighters (n = 1,430; 19.40%), and severe externalizers (n = 1,020, 12.51%). These subgroups differed on demographic, behavioral, and psychosocial characteristics. Findings are discussed in light of prevention and focused deterrence

ProtocadherinX/Y, a Candidate Gene-Pair for Schizophrenia and Schizoaffective Disorder: A DHPLC Investigation of Gonomic Sequence

Protocadherin X and Protocadherin Y (PCDHX and PCDHY) are cell-surface adhesion molecules expressed predominantly in the brain. The PCDHX/Y gene-pair was generated by an X-Y translocation approximately 3 million years ago (MYA) that gave rise to the Homo sapiens-specific region of Xq21.3 and Yp11.2 homology. Genes within this region are expected to code for sexually dimorphic human characteristics, including, for example, cerebral asymmetry a dimension of variation that has been suggested is relevant to psychosis. We examined differences in patients with schizophrenic or schizoaffective psychosis in the genomic sequence of PCDHX and PCDHY in coding and adjacent intronic sequences using denaturing high performance liquid chromatography (DHPLC). Three coding variants were detected in PCDHX and two in PCDHY. However, neither the coding variants nor the intronic polymorphisms could be related to psychosis within families. Low sequence variation suggests selective pressure against sequence change in modern humans in contrast to the structural chromosomal and sequence changes including fixed X-Y differences that occurred in this region earlier in hominid evolution. Our findings exclude sequence variation in PCDHX/Y as relevant to the aetiology of psychosis. However, we note the unusual status of this region with respect to X-inactivation. Further investigation of the epigenetic control of PCDHX/Y in relation to psychosis is warran

Trends and correlates of substance use disorders among probationers and parolees in the United States 2002–2014

BACKGROUND: Substance use and crime/recidivism are irrevocably linked. We explore the nuances of this association by highlighting the prevalence, trends, and correlates of substance use dsorders in a large group of probationers/parolees. METHODS: We examined SUDs among probationers and parolees in the United States using data from the National Study on Drug Use and Health (NSDUH). Logistic regression models were computed to examine eight distinct outcomes: alcohol abuse, illicit drug abuse, marijuana/hashish abuse, comorbid alcohol and illicit drug abuse, alcohol dependence, illicit drug dependence, marijuana/hashish dependence, and comorbid alcohol and illicit drug dependence. RESULTS: Probationers/parolees have high prevalence rates across all SUDs categories and these trends have been relatively constant. Prevalence rates for alcohol abuse and dependence are two to six times higher than for marijuana and other illicit drug abuse and dependence. Key correlates of substance abuse for probationers/parolees include: age, gender, race/ethnicity, education, income, risk propensity, crime/violence measures, and comorbid substance abuse. Similar correlates were found for substance dependence, in addition to employment and mental health treatment. CONCLUSIONS: This study indicates that SUDs are higher among probationer/parolees as compared to their non-supervised counterparts − between four and nine times higher − and these levels have changed little in recent years. Effectively responding to SUDs in this population may enhance adherence to supervision requirements, prevent recidivism, and improve public safety. We may be better served using limited funds for further development of evidence-based policies and programs, such as drug courts, which demonstrate reductions in both drug use and recidivism

Redistribution of critical major histocompatibility complex and T cell receptor-binding functions of residues in an antigenic sequence after biterminal substitution

Residues critical for establishing a trimolecular interaction with a major histocompatibility complex (MHC)-encoded receptor and a T cell antigen receptor (TcR) were determined for an antigenic nonapeptide. The N-terminal residue proved to be involved in binding of the peptide to both receptors and the C-terminal residue was essential for MHC binding. While substitution of either of these critical terminal residues by alanine resulted in an almost complete loss of peptide antigenicity, simultaneous substitution of both created a new functional ligand for the same MHC molecule and the same TcR. Notably, in the biterminally substituted peptide, the core residues took on new roles in the trimolecular interaction in that a residue critical in the authentic nonapeptide for TcR binding became critical for MHC binding and former spacer residues became essential to various degrees for the interaction with either receptor or both. Thus, apparently, the loss of the terminal residues' contribution was at least partially compensated by a redistribution of the roles among the remaining residues. These results reflect a cooperative contribution of all residues of an antigenic peptide to its binding to both receptors and thus challenge a static definition of agretope and epitope as MHC and TcR binding sites

Handgun carrying among white youth increasing in the United States: new evidence from the national survey on drug use and health 2002–2013

The objective of the present study was to examine trends and correlates of handgun carrying among adolescents ages 12–17 in the United States. Data was derived from the National Survey on Drug Use and Health (NSDUH) involving non-Hispanic White, African American, and Hispanic respondents ages 12–17 (n = 197,313) and spanning the years 2002–2013. Logistic regression was used to examine significance of trend year and correlates of previous 12-month handgun carrying. The overall self-reported prevalence of handgun carrying was 3.4%. The prevalence of handgun carrying during 2004–2005 was significantly higher for African-Americans (4.39%) compared to non-Hispanic Whites (3.03%). However, by 2012–2013, non-Hispanic Whites (4.08%) completely diverged and reported carrying handguns significantly more than both African-American (2.96%) and Hispanic (2.82%) youth. Male gender and a number of externalizing behaviors were significant correlates of handgun carrying; however, we also found evidence of differential correlates with regard to such factors as drug selling, parental affirmation, and income by race/ethnicity. To our knowledge, this is the largest study of handgun carrying among youth in the United States. Findings indicate that although at historically low levels handgun carrying is on the rise but only among non-Hispanic Whites. Differential correlates among racial/ethnic groups suggest prevention programming and policies may need modifications depending on group and geographic locale targeted.R25 DA030310 - National Institute on Drug Abuse at the National Institutes of Healt

Factor structure and familiality of first-rank symptoms in sibling pairs with schizophrenia and schizoaffective disorder

Background Since their introduction as diagnostic criteria by Schneider in 1937, nuclear symptoms have played a key role in concepts of schizophrenia, but their relationship to each other and to genetic predisposition has been unclear. Aims To ascertain the factor structure and familiality of nuclear symptoms. Methods Nuclear (Schneiderian) symptoms were extracted from case notes and interviews in a study of 103 sibling pairs with DSM-III-R schizophrenia or schizoaffective disorder. Results Principal components analysis demonstrated two major factors : one, accounting for about 50% of the variance, groups thought withdrawal, insertion and broadcasting, with delusions of control ; and the second, accounting for <20% of the variance, groups together third-person voices, thought echo and running commentary. Factor I was significantly correlated within sibling pairs. Conclusions The correlation within sibling pairs suggests that, contrary to the conclusion of some previous studies, some nuclear symptoms do show a degree of familiality and therefore perhaps heritability