bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene selection via the BAHSIC family of algorithms
Authors: Song Le , Bedo Justin , Borgwardt Karsten M. , Gretton Arthur , Smola Alex 
Published: July 2007

Abstract
Motivation: Identifying significant genes among thousands of sequences on a microarray is a central challenge for cancer research in bioinformatics. The ultimate goal is to detect the genes that are involved in disease outbreak and progression. A multitude of methods have been proposed for this task of feature selection, yet the selected gene lists differ greatly between different methods. To accomplish biologically meaningful gene selection from microarray data, we have to understand the theoretical connections and the differences between these methods. In this article, we define a kernel-based framework for feature selection based on the Hilbert–Schmidt independence criterion and backward elimination, called BAHSIC. We show that several well-known feature selectors are instances of BAHSIC, thereby clarifying their relationship. Furthermore, by choosing a different kernel, BAHSIC allows us to easily define novel feature selection algorithms. As a further advantage, feature selection via BAHSIC works directly on multiclass problems.
Results: In a broad experimental evaluation, the members of the BAHSIC family reach high levels of accuracy and robustness when compared to other feature selection techniques. Experiments show that features selected with a linear kernel provide the best classification performance in general, but if strong non-linearities are present in the data then non-linear kernels can be more suitable.
Availability: Accompanying homepage is http://www.dbs.ifi.lmu.de/~borgward/BAHSIC
Contact: kb@dbs.ifi.lmu.de
Supplementary information: Supplementary data are available at Bioinformatics online.
Reconstructing sibling relationships in wild populations
Authors: Berger-Wolf Tanya Y. , Sheikh Saad I. , DasGupta Bhaskar , Ashley Mary V. , Caballero Isabel C. , Chaovalitwongse Wanpracha , Putrevu S. Lahari 
Published: July 2007

Abstract
Reconstruction of sibling relationships from genetic data is an important component of many biological applications. In particular, the growing application of molecular markers (microsatellites) to study wild populations of plant and animals has created the need for new computational methods of establishing pedigree relationships, such as sibgroups, among individuals in these populations. Most current methods for sibship reconstruction from microsatellite data use statistical and heuristic techniques that rely on a priori knowledge about various parameter distributions. Moreover, these methods are designed for data with large number of sampled loci and small family groups, both of which typically do not hold for wild populations. We present a deterministic technique that parsimoniously reconstructs sibling groups using only Mendelian laws of inheritance. We validate our approach using both simulated and real biological data and compare it to other methods. Our method is highly accurate on real data and compares favorably with other methods on simulated data with few loci and large family groups. It is the only method that does not rely on a priori knowledge about the population under study. Thus, our method is particularly appropriate for reconstructing sibling groups in wild populations.
Contact: tanyabw@uic.edu
Inferring missing genotypes in large SNP panels using fast nearest-neighbor searches over sliding windows
Authors: Roberts Adam , McMillan Leonard , Wang Wei , Parker Joel , Rusyn Ivan , Threadgill David 
Published: July 2007

Abstract
Motivation: Typical high-throughput genotyping techniques produce numerous missing calls that confound subsequent analyses, such as disease association studies. Common remedies for this problem include removing affected markers and/or samples or, otherwise, imputing the missing data. On small marker sets imputation is frequently based on a vote of the K-nearest-neighbor (KNN) haplotypes, but this technique is neither practical nor justifiable for large datasets.
Results: We describe a data structure that supports efficient KNN queries over arbitrarily sized, sliding haplotype windows, and evaluate its use for genotype imputation. The performance of our method enables exhaustive exploration over all window sizes and known sites in large (150K, 8.3M) SNP panels. We also compare the accuracy and performance of our methods with competing imputation approaches.
Availability: A free open source software package, NPUTE, is available at http://compgen.unc.edu/software, for non-commercial uses.
Contact: mcmillan@cs.unc.edu
RankMotif++: a motif-search algorithm that accounts for relative ranks of K-mers in binding transcription factors
Authors: Chen Xiaoyu , Hughes Timothy R. , Morris Quaid 
Published: July 2007

Abstract
Motivation: The sequence specificity of DNA-binding proteins is typically represented as a position weight matrix in which each base position contributes independently to relative affinity. Assessment of the accuracy and broad applicability of this representation has been limited by the lack of extensive DNA-binding data. However, new microarray techniques, in which preferences for all possible K-mers are measured, enable a broad comparison of both motif representation and methods for motif discovery. Here, we consider the problem of accounting for all of the binding data in such experiments, rather than the highest affinity binding data. We introduce the RankMotif++, an algorithm designed for finding motifs whenever sequences are associated with a semi-quantitative measure of protein-DNA-binding affinity. RankMotif++ learns motif models by maximizing the likelihood of a set of binding preferences under a probabilistic model of how sequence binding affinity translates into binding preference observations. Because RankMotif++ makes few assumptions about the relationship between binding affinity and the semi-quantitative readout, it is applicable to a wide variety of experimental assays of DNA-binding preference.
Results: By several criteria, RankMotif++ predicts binding affinity better than two widely used motif finding algorithms (MDScan, MatrixREDUCE) or more recently developed algorithms (PREGO, Seed and Wobble), and its performance is comparable to a motif model that separately assigns affinities to 8-mers. Our results validate the PWM model and provide an approximation of the precision and recall that can be expected in a genomic scan.
Availability: RankMotif++ is available upon request.
Contact: quaid.morris@utoronto.ca
Supplementary information: Supplementary data are available at Bioinformatics online.
A graph-based approach to systematically reconstruct human transcriptional regulatory modules
Authors: Yan Xifeng , Mehan Michael R. , Huang Yu , Waterman Michael S. , Yu Philip S. , Zhou Xianghong Jasmine 
Published: July 2007

Abstract
Motivation: A major challenge in studying gene regulation is to systematically reconstruct transcription regulatory modules, which are defined as sets of genes that are regulated by a common set of transcription factors. A commonly used approach for transcription module reconstruction is to derive coexpression clusters from a microarray dataset. However, such results often contain false positives because genes from many transcription modules may be simultaneously perturbed upon a given type of conditions. In this study, we propose and validate that genes, which form a coexpression cluster in multiple microarray datasets across diverse conditions, are more likely to form a transcription module. However, identifying genes coexpressed in a subset of many microarray datasets is not a trivial computational problem.
Results: We propose a graph-based data-mining approach to efficiently and systematically identify frequent coexpression clusters. Given m microarray datasets, we model each microarray dataset as a coexpression graph, and search for vertex sets which are frequently densely connected across ⌈ θ m ⌉ datasets (0 ≤ θ ≤ 1). For this novel graph-mining problem, we designed two techniques to narrow down the search space: (1) partition the input graphs into (overlapping) groups sharing common properties; (2) summarize the vertex neighbor information from the partitioned datasets onto the ‘Neighbor Association Summary Graph's for effective mining. We applied our method to 105 human microarray datasets, and identified a large number of potential transcription modules, activated under different subsets of conditions. Validation by ChIP-chip data demonstrated that the likelihood of a coexpression cluster being a transcription module increases significantly with its recurrence. Our method opens a new way to exploit the vast amount of existing microarray data accumulation for gene regulation study. Furthermore, the algorithm is applicable to other biological networks for approximate network module mining.
Availability: http://zhoulab.usc.edu/NeMo/
Contact: xjzhou@usc.edu
Haplotype inference for present–absent genotype data using previously identified haplotypes and haplotype patterns
Authors: Yoo Yun Joo , Tang Jianming , Kaslow Richard A. , Zhang Kui 
Published: July 2007

AbstractMotivation: Killer immunoglobulin-like receptor (KIR) genes vary considerably in their presence or absence on a specific regional haplotype. Because presence or absence of these genes is largely detected using locus-specific genotyping technology, the distinction between homozygosity and hemizygosity is often ambiguous. The performance of methods for haplotype inference (e.g. PL-EM, PHASE) for KIR genes may be compromised due to the large portion of ambiguous data. At the same time, many haplotypes or partial haplotype patterns have been previously identified and can be incorporated to facilitate haplotype inference for unphased genotype data. To accommodate the increased ambiguity of present–absent genotyping of KIR genes, we developed a hybrid approach combining a greedy algorithm with the Expectation-Maximization (EM) method for haplotype inference based on previously identified haplotypes and haplotype patterns.Results: We implemented this algorithm in a software package named HAPLO-IHP (Haplotype inference using identified haplotype patterns) and compared its performance with that of HAPLORE and PHASE on simulated KIR genotypes. We compared five measures in order to evaluate the reliability of haplotype assignments and the accuracy in estimating haplotype frequency. Our method outperformed the two existing techniques by all five measures when either 60 % or 25 % of previously identified haplotypes were incorporated into the analyses.Availability: The HAPLO-IHP is available at http://www.soph.uab.edu/Statgenetics/People/KZhang/HAPLO-IHP/index.htmlContact: KZhang@ms.soph.uab.eduSupplementary information: Supplementary data are available at Bioinformatics online.
miniTUBA: medical inference by network integration of temporal data using Bayesian analysis
Authors: Xiang Zuoshuang , Minter Rebecca M. , Bi Xiaoming , Woolf Peter J. , He Yongqun 
Published: July 2007

AbstractMotivation: Many biomedical and clinical research problems involve discovering causal relationships between observations gathered from temporal events. Dynamic Bayesian networks are a powerful modeling approach to describe causal or apparently causal relationships, and support complex medical inference, such as future response prediction, automated learning, and rational decision making. Although many engines exist for creating Bayesian networks, most require a local installation and significant data manipulation to be practical for a general biologist or clinician. No software pipeline currently exists for interpretation and inference of dynamic Bayesian networks learned from biomedical and clinical data.Results: miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data.Availability: miniTUBA is available at http://www.minituba.orgContact: yongqunh@med.umich.edu
APID2NET: unified interactome graphic analyzer
Authors: Hernandez-Toro Juan , Prieto Carlos , De Las Rivas Javier 
Published: July 2007

AbstractMotivation: Exploration and analysis of interactome networks at systems level requires unification of the biomolecular elements and annotations that come from many different high-throughput or small-scale proteomic experiments. Only such integration can provide a non-redundant and consistent identification of proteins and interactions. APID2NET is a new tool that works with Cytoscape to allow surfing unified interactome data by querying APID server (http://bioinfow.dep.usal.es/apid/) to provide interactive analysis of protein–protein interaction (PPI) networks. The program is designed to visualize, explore and analyze the proteins and interactions retrieved, including the annotations and attributes associated to them, such as: GO terms, InterPro domains, experimental methods that validate each interaction, PubMed IDs, UniProt IDs, etc. The tool provides interactive graphical representation of the networks with all Cytoscape capabilities, plus new automatic tools to find concurrent functional and structural attributes along all protein pairs in a network.Availability: http://bioinfow.dep.usal.es/apid/apid2net.htmlContact: jrivas@usal.esSupplementary information: Installation Guide and User's Guide are supplied at the Web site indicated above.
Underwater television as a fishery-independent method for stock assessment of Norway lobster (Nephrops norvegicus) in the central Adriatic Sea (Italy)
Authors: Morello Elisabetta B. , Froglia Carlo , Atkinson R. J. A. 
Published: July 2007

Abstract
Morello, E. B., Froglia, C., and Atkinson, R. J. A. 2007. Underwater television as a fishery-independent method for stock assessment of Norway lobster (Nephrops norvegicus) in the central Adriatic Sea (Italy). – ICES Journal of Marine Science, 64: 1116–1123. Norway lobster is of great commercial importance throughout the NE Atlantic and Mediterranean, where it lives in burrows in muddy sediments. The fact that the species is caught in commercial gear only when it emerges from its burrow and the absence of hard structures available for age determination complicate the application of normal fishery-dependent stock-assessment methodologies. This study provides more evidence of the usefulness of underwater television surveys as a fishery-independent technique to assess the Nephrops stocks of the Adriatic Sea. The results are compared with those of previous studies, and the advantages and disadvantages of using such methodology discussed in an Adriatic context.
Quantitative diet assessment of wobbegong sharks (genus Orectolobus) in New South Wales, Australia
Authors: Huveneers Charlie , Otway Nicholas M. , Gibbs Susan E. , Harcourt Robert G. 
Published: July 2007

AbstractHuveneers, C., Otway, N. M., Gibbs, S. E., and Harcourt, R. G. 2007. Quantitative diet assessment of wobbegong sharks (genus Orectolobus) in New South Wales, Australia. – ICES Journal of Marine Science, 64: 1272–1281. The diets of three species of wobbegong (Orectolobus ornatus, O. maculatus, and O. halei) in New South Wales, Australia, were investigated using stomach contents from specimens caught by commercial fishers. Some 80% of wobbegongs caught by commercial setline, and 60% caught by trap or scuba diving, had empty stomachs, most likely due to regurgitation. Wobbegongs were frequently hooked in the stomach (80–90% of the catch), potentially contributing to the greater proportion of empty stomachs compared with other species of shark. The diet of all three species was primarily osteichthyans, but with some cephalopods and chondrichthyans. Interspecific differences in the diets were related to total length of the shark. Octopuses were more frequent in the diet of O. ornatus (dwarf ornate wobbegong) than other wobbegong species, possibly through the smaller adult size facilitating capture of octopuses in small holes/crevices. Orectolobus halei fed more frequently on pelagic species and chondrichthyans, possibly because of their greater mobility. Wobbegongs feed at a high trophic level, and their removal from their ecosystem may impact lower trophic levels.
Basic mechanisms of high‐risk human papillomavirus‐induced carcinogenesis: Roles of E6 and E7 proteins
Authors: Narisawa‐Saito Mako , Kiyono Tohru 
Published: July 2007

Human papillomaviruses (HPV) are believed to be the primary causal agents for development of pre‐neoplastic and malignant lesions of the uterine cervix, and high‐risk types such as type 16 and 18 are associated with more than 90% of all cervical carcinomas. The E6 and E7 genes of HPV are thought to play causative roles, since E6 promotes the degradation of p53 through its interaction with E6AP, an E3 ubiquitin ligase, whereas E7 binds to the retinoblastoma protein (pRb) and disrupts its complex formation with E2F transcription factors. Although prophylactic vaccines have become available, it is still necessary to clarify the mechanisms of HPV‐induced carcinogenesis because of the widespread nature of HPV infection. Approximately 493 000 new cases of cervical cancer are diagnosed each year with approximately 274 000 mortalities due to invasive cervical cancer. In the present article, the mechanisms of HPV16 E6‐ and E7‐induced multistep carcinogenesis and recently identified functions of these onco‐proteins are reviewed. (Cancer Sci 2007; 98: 1505–1511)
The cost‐effectiveness of four treatments for marijuana dependence
Authors: Olmstead Todd A. , Sindelar Jody L. , Easton Caroline J. , Carroll Kathleen M. 
Published: July 2007

ABSTRACTAim To analyze data from a randomized clinical trial to determine the cost‐effectiveness of using contingency management (CM) and motivational/skills building therapy (motivational enhancement therapy/cognitive‐behavioral therapy: MET/CBT) to treat young adults with marijuana dependence.Participants, design and measurements A total of 136 marijuana‐dependent young adults, all referred by the criminal justice system, were randomized to one of four treatment conditions: MET/CBT with CM, MET/CBT without CM, drug counseling (DC) with CM and DC without CM. Patient outcome measures include the longest duration of confirmed marijuana abstinence (LDA) during treatment and the total number of marijuana‐free urine specimens provided during treatment. Costs were collected retrospectively from the provider and include the costs of therapy, patient drug testing, and those associated with the incentives component (value of vouchers, time to administer the voucher system).Setting Out‐patient substance abuse clinic in New Haven, Connecticut, USA.Findings Which treatment is the most cost‐effective depends on the threshold values of an additional week of LDA or an additional marijuana‐free urine specimen. For example, the most effective treatment, MET/CBT with CM, was also the most cost‐effective treatment at the highest threshold values, while the least effective treatment, DC, was the most cost‐effective at the lowest values. Because consensus threshold values for these patient outcomes do not exist, results are presented showing the ranges of values over which each treatment would be considered cost‐effective compared to the others. Acceptability curves are presented to show the decision uncertainty associated with these ranges. The results are shown to be robust to (i) sensitivity analyses on several key cost parameters and (ii) patient outcomes measured during the 6‐month follow‐up period.Conclusions This study uses incremental cost‐effectiveness ratios and acceptability curves to shed light on the relative cost‐effectiveness of four interventions for treating young adults with marijuana dependence. Given the relatively small and specialized nature of our study sample, and the fact that we examined a CM procedure with a single reinforcement schedule, additional studies are warranted to determine the reliability and generalizability of our results both to alternative marijuana‐using populations and to CM procedures with alternative incentive parameters. Nevertheless, the relative durability of effects of MET/CBT compared to DC through the 6‐month follow‐up, and its cost‐effectiveness over a comparatively wide range of threshold values, underscores the promise of this approach.
The role of plant defence proteins in fungal pathogenesis
Authors: FERREIRA RICARDO B. , MONTEIRO SARA , FREITAS REGINA , SANTOS CLÁUDIA N. , CHEN ZHENJIA , BATISTA LUÍS M. , DUARTE JOÃO , BORGES ALEXANDRE , TEIXEIRA ARTUR R. 
Published: July 2007

SUMMARYIt is becoming increasingly evident that a plant–pathogen interaction may be compared to an open warfare, whose major weapons are proteins synthesized by both organisms. These weapons were gradually developed in what must have been a multimillion‐year evolutionary game of ping‐pong. The outcome of each battle results in the establishment of resistance or pathogenesis. The plethora of resistance mechanisms exhibited by plants may be grouped into constitutive and inducible, and range from morphological to structural and chemical defences. Most of these mechanisms are defensive, exhibiting a passive role, but some are highly active against pathogens, using as major targets the fungal cell wall, the plasma membrane or intracellular targets. A considerable overlap exists between pathogenesis‐related (PR) proteins and antifungal proteins. However, many of the now considered 17 families of PR proteins do not present any known role as antipathogen activity, whereas among the 13 classes of antifungal proteins, most are not PR proteins. Discovery of novel antifungal proteins and peptides continues at a rapid pace. In their long coevolution with plants, phytopathogens have evolved ways to avoid or circumvent the plant defence weaponry. These include protection of fungal structures from plant defence reactions, inhibition of elicitor‐induced plant defence responses and suppression of plant defences. A detailed understanding of the molecular events that take place during a plant–pathogen interaction is an essential goal for disease control in the future.