Local Geometry of Multiattribute Tradeoff Preferences

PhD thesisExisting preference reasoning systems have been successful insimple domains. Broader success requires more natural and moreexpressive preference representations. This thesis develops arepresentation of logical preferences that combines numericaltradeoff ratios between partial outcome descriptions withqualitative preference information. We argue our system is uniqueamong preference reasoning systems; previous work has focused onqualitative or quantitative preferences, tradeoffs, exceptions andgeneralizations, or utility independence, but none have combinedall of these expressions under a unified methodology.We present new techniques for representing and giving meaning toquantitative tradeoff statements between different outcomes. Thetradeoffs we consider can be multi-attribute tradeoffs relatingmore than one attribute at a time, they can refer to discrete orcontinuous domains, be conditional or unconditional, andquantified or qualitative. We present related methods ofrepresenting judgments of attribute importance. We then buildupon a methodology for representing arbitrary qualitative ceteris paribuspreference, or preferences ``other things being equal," aspresented in MD04. Tradeoff preferences inour representation are interpreted as constraints on the partialderivatives of the utility function. For example, a decision makercould state that ``Color is five times as important as price,availability, and time," a sentiment one might express in thecontext of repainting a home, and this is interpreted asindicating that utility increases in the positive color directionfive times faster than utility increases in the positive pricedirection. We show that these representations generalize both theeconomic notion of marginal rates of substitution and previousrepresentations of preferences in AI

The local geometry of multiattribute tradeoff preferences

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 125-129).Existing preference reasoning systems have been successful in simple domains. Broader success requires more natural and more expressive preference representations. This thesis develops a representation of logical preferences that combines numerical tradeoff ratios between partial outcome descriptions with qualitative preference information. We argue our system is unique among preference reasoning systems; previous work has focused on qualitative or quantitative preferences, tradeoffs, exceptions and generalizations, or utility independence, but none have combined all of these expressions under a unified methodology. We present new techniques for representing and giving meaning to quantitative tradeoff statements between different outcomes. The tradeoffs we consider can be multi-attribute tradeoffs relating more than one attribute at a time, they can refer to discrete or continuous domains, be conditional or unconditional, and quantified or qualitative. We present related methods of representing judgments of attribute importance. We then build upon a methodology for representing arbitrary qualitative ceteris paribus preference, or preferences "other things being equal," as presented in [MD04].(cont.) Tradeoff preferences in our representation are interpreted as constraints on the partial derivatives of the utility function. For example, a decision maker could state that "Color is five times as important as price, availability, and time," a sentiment one might express in the context of repainting a home, and this is interpreted as indicating that utility increases in the positive color direction five times faster than utility increases in the positive price direction. We show that these representations generalize both the economic notion of marginal rates of substitution and previous representations of preferences in AI.by Michael McGeachie.Ph.D

Utility functions for ceteris paribus preferences

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (p. 101-103).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Ceteris paribus preference statements concisely represent preferences over outcomes or goals in a way natural to human thinking. Many decision making methods require an efficient method for comparing the desirability of two arbitrary goals. We address this need by presenting an algorithm for converting a set of qualitative ceteris paribus preferences into a quantitative utility function. Our algorithm is complete for a finite universe of binary features. Constructing the utility function can, in the worst case, take time exponential in the number of features. Common forms of independence conditions reduce the computational burden. We present heuristics using utility independence and constraint based search to achieve efficient utility functions.by Michael McGeachie.S.M

CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com

Bridging (thionylimido)metal complexes

L.J.R.M. is grateful to EPSRC for a provision of Ph.D. funding. M.B. thanks the School of Chemistry and EaStCHEM for support.We report the first examples of the thionylimido ligand acting as a μ2-bridging ligand between two transition-metal centers; using Cp2Ti(NSO)2, we describe bi- and tetrametallic systems.Publisher PDFPeer reviewe

Patterns of Growth and Decline in Lung Function in Persistent Childhood Asthma

BACKGROUND: Tracking longitudinal measurements of growth and decline in lung function in patients with persistent childhood asthma may reveal links between asthma and subsequent chronic airflow obstruction. METHODS: We classified children with asthma according to four characteristic patterns of lung-function growth and decline on the basis of graphs showing forced expiratory volume in 1 second (FEV1), representing spirometric measurements performed from childhood into adulthood. Risk factors associated with abnormal patterns were also examined. To define normal values, we used FEV1 values from participants in the National Health and Nutrition Examination Survey who did not have asthma. RESULTS: Of the 684 study participants, 170 (25%) had a normal pattern of lung-function growth without early decline, and 514 (75%) had abnormal patterns: 176 (26%) had reduced growth and an early decline, 160 (23%) had reduced growth only, and 178 (26%) had normal growth and an early decline. Lower baseline values for FEV1, smaller bronchodilator response, airway hyperresponsiveness at baseline, and male sex were associated with reduced growth (P \u3c 0.001 for all comparisons). At the last spirometric measurement (mean [+/-SD] age, 26.0+/-1.8 years), 73 participants (11%) met Global Initiative for Chronic Obstructive Lung Disease spirometric criteria for lung-function impairment that was consistent with chronic obstructive pulmonary disease (COPD); these participants were more likely to have a reduced pattern of growth than a normal pattern (18% vs. 3%, P \u3c 0.001). CONCLUSIONS: Childhood impairment of lung function and male sex were the most significant predictors of abnormal longitudinal patterns of lung-function growth and decline. Children with persistent asthma and reduced growth of lung function are at increased risk for fixed airflow obstruction and possibly COPD in early adulthood. (Funded by the Parker B. Francis Foundation and others; ClinicalTrials.gov number, NCT00000575.)

Thionylimido complexes

An improved route to d-block and main group NSO complexes is presented including the synthesis of the first antimony(V) complexes, (Ar3Sb(NSO)2), and copper examples (CuBipy(PPh3)NSO). The structures of eight complexes are reported. The observed variation in M-N-S bond angles is due to the combination of orbital overlap (ligand-to-metal bonding) and the degree of ionicity of the bonding.Publisher PDFPeer reviewe

Pharmacogenetics of inhaled corticosteroids and exacerbation risk in adults with asthma

Background: Inhaled corticosteroids (ICS) are a cornerstone of asthma treatment. However, their efficacy is characterized by wide variability in individual responses. Objective: We investigated the association between genetic variants and risk of exacerbations in adults with asthma and how this association is affected by ICS treatment. Methods: We investigated the pharmacogenetic effect of 10 single nucleotide polymorphisms (SNPs) selected from the literature, including SNPs previously associated with response to ICS (assessed by change in lung function or exacerbations) and novel asthma risk alleles involved in inflammatory pathways, within all adults with asthma from the Dutch population-based Rotterdam study with replication in the American GERA cohort. The interaction effects of the SNPs with ICS on the incidence of asthma exacerbations were assessed using hurdle models adjusting for age, sex, BMI, smoking and treatment step according to the GINA guidelines. Haplotype analyses were also conducted for the SNPs located on the same chromosome. Results: rs242941 (CRHR1) homozygotes for the minor allele (A) showed a significant, replicated increased risk for frequent exacerbations (RR = 6.11, P < 0.005). In contrast, rs1134481T allele within TBXT (chromosome 6, member of a family associated with embryonic lung development) showed better response with ICS. rs37973 G allele (GLCCI1) showed a significantly poorer response on ICS within the discovery cohort, which was also significant but in the opposite direction in the replication cohort. Conclusion: rs242941 in CRHR1 was associated with poor ICS response. Conversely, TBXT variants were associated with improved ICS response. These associations may reveal specific endotypes, potentially allowing prediction of exacerbation risk and ICS response

Expression of SMARCD1 interacts with age in association with asthma control on inhaled corticosteroid therapy.

BackgroundGlobal gene expression levels are known to be highly dependent upon gross demographic features including age, yet identification of age-related genomic indicators has yet to be comprehensively undertaken in a disease and treatment-specific context.MethodsWe used gene expression data from CD4+ lymphocytes in the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), an open-access collection of subjects participating in genetic studies of asthma with available gene expression data. Replication population participants were Puerto Rico islanders recruited as part of the ongoing Genes environments &amp; Admixture in Latino Americans (GALA II), who provided nasal brushings for transcript sequencing. The main outcome measure was chronic asthma control as derived by questionnaires. Genomic associations were performed using regression of chronic asthma control score on gene expression with age in years as a covariate, including a multiplicative interaction term for gene expression times age.ResultsThe SMARCD1 gene (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily D member 1) interacted with age to influence chronic asthma control on inhaled corticosteroids, with a doubling of expression leading to an increase of 1.3 units of chronic asthma control per year (95% CI [0.86, 1.74], p = 6 × 10- 9), suggesting worsening asthma control with increasing age. This result replicated in GALA II (p = 3.8 × 10- 8). Cellular assays confirmed the role of SMARCD1 in glucocorticoid response in airway epithelial cells.ConclusionFocusing on age-dependent factors may help identify novel indicators of asthma medication response. Age appears to modulate the effect of SMARCD1 on asthma control with inhaled corticosteroids

Joint GWAS Analysis: Comparing similar GWAS at different genomic resolutions identifies novel pathway associations with six complex diseases

We show here that combining two existing genome wide association studies (GWAS) yields additional biologically relevant information, beyond that obtained by either GWAS separately. We propose Joint GWAS Analysis, a method that compares a pair of GWAS for similarity among the top SNP associations, top genes identified, gene functional clusters, and top biological pathways. We show that Joint GWAS Analysis identifies additional enriched biological pathways that would be missed by traditional Single-GWAS analysis. Furthermore, we examine the similarities of six complex genetic disorders at the SNP-level, gene-level, gene-cluster-level, and pathway-level. We make concrete hypotheses regarding novel pathway associations for several complex disorders considered, based on the results of Joint GWAS Analysis. Together, these results demonstrate that common complex disorders share substantially more genomic architecture than has been previously realized and that the meta-analysis of GWAS needs not be limited to GWAS of the same phenotype to be informative