Choosing the right path: enhancement of biologically relevant sets of genes or proteins using pathway structure.
Ontology highlight
ABSTRACT:
SUBMITTER: Thomas R
PROVIDER: S-EPMC2688935 | biostudies-literature | 2009
REPOSITORIES: biostudies-literature
Publications
Choosing the right path: enhancement of biologically relevant sets of genes or proteins using pathway structure.
Thomas Reuben R Gohlke Julia M JM Stopper Geffrey F GF Parham Frederick M FM Portier Christopher J CJ
Genome biology 20090424 4
A method is proposed that finds enriched pathways relevant to a studied condition using the measured molecular data and also the structural information of the pathway viewed as a network of nodes and edges. Tests are performed using simulated data and genomic data sets and the method is compared to two existing approaches. The analysis provided demonstrates the method proposed is very competitive with the current approaches and also provides biologically relevant results. ...[more]
Similar Datasets
Project description:The ability to discriminate changes in the fine structure of complex sounds is well developed in birds. However, the precise limit of this discrimination ability and how it is used in the context of natural communication remains unclear. Here we describe natural variability in acoustic fine structure of male and female zebra finch calls. Results from psychoacoustic experiments demonstrate that zebra finches are able to discriminate extremely small differences in fine structure, which are on the order of the variation in acoustic fine structure that is present in their vocal signals. Results from signal analysis methods also suggest that acoustic fine structure may carry information that distinguishes between biologically relevant categories including sex, call type and individual identity. Combined, our results are consistent with the hypothesis that zebra finches can encode biologically relevant information within the fine structure of their calls. This study provides a foundation for our understanding of how acoustic fine structure may be involved in animal communication.
| S-EPMC5906677 | biostudies-literature
Project description:Oxidative DNA-protein cross-links have received less attention than other types of DNA damage and remain as one of the least understood types of oxidative lesion. A model system using ribonuclease A and a 27-nucleotide DNA was used to determine the propensity of oxidative cross-linking to occur in the presence of oxidants. Cross-link formation was examined using four different oxidation systems that generate singlet oxygen, superoxide, and metal-based Fenton reactions. It is shown that oxidative cross-linking occurs in yields ranging from 14% to a maximal yield of 61% in all oxidative systems when equivalent concentrations of DNA and protein are present. Because singlet oxygen is the most efficient oxidation system in generating DNA-protein cross-links, it was chosen for further analyses. Cross-linking occurred with single-stranded DNA binding protein and not with bovine serum albumin. Addition of salt lowered nonspecific binding affinity and lowered cross-link yield by up to 59%. The yield of cross-linking increased with increased ratios of protein compared with DNA. Cross-linking was highly dependent on the number of guanines in a DNA sequence. Loss of guanine content on the 27-nucleotide DNA led to nearly complete loss in cross-linking, while primer extension studies showed cross-links to predominantly occur at guanine base on a 100-nucleotide DNA. The chemical species generated were examined using two peptides derived from the ribonuclease A sequence, N-acetyl-AAAKF and N-acetyl-AYKTT, which were cross-linked to 2'-deoxyguanosine. The cross-link products were spiroiminodihydantoin, guanidinohydantoin, and tyrosyl-based adducts. Formation of tyrosine-based adducts may be competitive with the more well-studied lysine-based cross-links. We conclude that oxidative cross-links may be present at high levels in cells since the propensity to oxidatively cross-link is high and so much of the genomic DNA is coated with protein.
| S-EPMC5507331 | biostudies-literature
Project description:Genome-wide association (GWA) studies of complex diseases including coronary heart disease (CHD) challenge investigators attempting to identify relevant genetic variants among hundreds of thousands of markers being tested. A selection strategy based purely on statistical significance will result in many false negative findings after adjustment for multiple testing. Thus, an integrated analysis using information from the learned genetic pathways, molecular functions, and biological processes is desirable. In this study, we applied a customized method, variable set enrichment analysis (VSEA), to the Framingham Heart Study data (404,467 variants, n=6421) to evaluate enrichment of genetic association in 1395 gene sets for their contribution to CHD. We identified 25 gene sets with nominal P<0.01; at least four sets are previously known for their roles in CHD: vascular genesis (GO:0001570), fatty-acid biosynthetic process (GO:0006633), fatty-acid metabolic process (GO:0006631), and glycerolipid metabolic process (GO:0046486). Although the four gene sets include 170 genes, only three of the genes contain a variant ranked among the top 100 in single-variant association tests of the 404,467 variants tested. Significant enrichment for novel gene sets less known for their importance to CHD were also identified: Rac 1 cell-motility signaling pathway (h_rac1 Pathway, P<0.001) and sulfur amino-acid metabolic process (GO:0000096, P<0.001). In summary, we showed that the pathway-based VSEA can help prioritize association signals in GWA studies by identifying biologically plausible targets for downstream searches of genetic variants associated with CHD.
| S-EPMC3477866 | biostudies-literature
Project description:Better characterization of binding sites in proteins and the ability to accurately predict their location and energetic properties are major challenges which, if addressed, would have many valuable practical applications. Unfortunately, reliable benchmark datasets of binding sites in proteins are still sorely lacking. Here, we present LigASite ('LIGand Attachment SITE'), a gold-standard dataset of binding sites in 550 proteins of known structures. LigASite consists exclusively of biologically relevant binding sites in proteins for which at least one apo- and one holo-structure are available. In defining the binding sites for each protein, information from all holo-structures is combined, considering in each case the quaternary structure defined by the PQS server. LigASite is built using simple criteria and is automatically updated as new structures become available in the PDB, thereby guaranteeing optimal data coverage over time. Both a redundant and a culled non-redundant version of the dataset is available at http://www.scmbb.ulb.ac.be/Users/benoit/LigASite. The website interface allows users to search the dataset by PDB identifiers, ligand identifiers, protein names or sequence, and to look for structural matches as defined by the CATH homologous superfamilies. The datasets can be downloaded from the website as Schema-validated XML files or comma-separated flat files.
| S-EPMC2238865 | biostudies-literature
Project description:BackgroundThe diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools.ResultsgeneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research.ConclusionsgeneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.
| S-EPMC3909759 | biostudies-literature
Project description:Radical and palliative treatments for non-small cell lung cancer (NSCLC) have faced a significant evolution during last decades, which in turn has modified their effects on the patient quality of life (QoL). QoL data collection is becoming methodologically rigorous, with published recommendations and societal statements. In lung cancer surgery, there is no standardization in collecting and analyzing this outcome yet. However, to face the evolution in lung cancer therapies, few initiatives like the European Organization for the Research and Treatment of Cancer (EORTC) lung cancer module update project or the Patient-Reported Outcomes Measurement Information System (PROMIS), have now the potential to help thoracic surgeons to collect QoL data with validated dynamic instruments to make this outcome comparable to the clinical ones. This review aims to give an overview of the available and most commonly used QoL questionnaires in lung cancer surgery in order to facilitate future research and practical implementation.
| S-EPMC7711361 | biostudies-literature
Project description:Previously, SAR models for carcinogenesis used descriptors that are essentially chemical descriptors. Herein we report the development of models with the cat-SAR expert system using biological descriptors (i.e., ligand-receptor interactions) rat mammary carcinogens. These new descriptors are derived from the virtual screening for ligand-receptor interactions of carcinogens, non-carcinogens, and mammary carcinogens to a set of 5494 target proteins. Leave-one-out validations of the ligand mammary carcinogen-non-carcinogen model had a concordance between experimental and predicted results of 71%, and the mammary carcinogen-non-mammary carcinogen model was 72% concordant. The development of a hybrid fragment-ligand model improved the concordances to 85 and 83%, respectively. In a separate external validation exercise, hybrid fragment-ligand models had concordances of 81 and 76%. Analyses of example rat mammary carcinogens including the food mutagen and oestrogenic compound PhIP, the herbicide atrazine, and the drug indomethacin; the ligand model identified a number of proteins associated with each compound that had previously been referenced in Medline in conjunction with the test chemical and separately with association to breast cancer. This new modelling approach can enhance model predictivity and help bridge the gap between chemical structure and carcinogenic activity by descriptors that are related to biological targets.
| S-EPMC3383027 | biostudies-literature
Project description:Frailty is a late-life syndrome of vulnerability to adverse health outcomes characterized by a phenotype that includes muscle weakness, fatigue, and inflammatory pathway activation. The identification of biologically relevant pathways that influence frailty is challenged by its biological complexity and the necessity in separating disease states from the syndrome of frailty. As with longevity research, genetic analyses may help to provide insights into biologically relevant pathways that contribute to frailty.Based on current understanding of the physiological basis of frailty, we hypothesize that variation in genes related to inflammation and muscle maintenance would associate with frailty. One thousand three hundred and fifty-four single-nucleotide polymorphisms were genotyped across 134 candidate genes using the Illumina Genotyping platform, and the rank order by strength of association between frailty and genotype was determined in a cross-sectional study.Although no single-nucleotide polymorphism reached study-wide significance after controlling family-wise false-discovery rate at 0.05, single-nucleotide polymorphisms within the 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), Caspase 8 (CASP8), CREB-binding protein (CREBBP), lysine acetyltransferase 2B (KAT2B), and beta-transducin repeat containing (BTRC) loci were among those strongly associated with frailty.The apoptosis- and transcription regulation-related pathways highlighted by this preliminary analysis were consistent with prior gene expression studies in a frail mouse model and provide useful etiological insights for future biological studies of frailty.
| S-EPMC3156628 | biostudies-literature
Project description:BackgroundThe use of 3-D similarity techniques in the analysis of biological data and virtual screening is pervasive, but what is a biologically meaningful 3-D similarity value? Can one find statistically significant separation between "active/active" and "active/inactive" spaces? These questions are explored using 734,486 biologically tested chemical structures, 1,389 biological assay data sets, and six different 3-D similarity types utilized by PubChem analysis tools.ResultsThe similarity value distributions of 269.7 billion unique conformer pairs from 734,486 biologically tested compounds (all-against-all) from PubChem were utilized to help work towards an answer to the question: what is a biologically meaningful 3-D similarity score? The average and standard deviation for the six similarity measures STST-opt, CTST-opt, ComboTST-opt, STCT-opt, CTCT-opt, and ComboTCT-opt were 0.54 ± 0.10, 0.07 ± 0.05, 0.62 ± 0.13, 0.41 ± 0.11, 0.18 ± 0.06, and 0.59 ± 0.14, respectively. Considering that this random distribution of biologically tested compounds was constructed using a single theoretical conformer per compound (the "default" conformer provided by PubChem), further study may be necessary using multiple diverse conformers per compound; however, given the breadth of the compound set, the single conformer per compound results may still apply to the case of multi-conformer per compound 3-D similarity value distributions. As such, this work is a critical step, covering a very wide corpus of chemical structures and biological assays, creating a statistical framework to build upon.The second part of this study explored the question of whether it was possible to realize a statistically meaningful 3-D similarity value separation between reputed biological assay "inactives" and "actives". Using the terminology of noninactive-noninactive (NN) pairs and the noninactive-inactive (NI) pairs to represent comparison of the "active/active" and "active/inactive" spaces, respectively, each of the 1,389 biological assays was examined by their 3-D similarity score differences between the NN and NI pairs and analyzed across all assays and by assay category types. While a consistent trend of separation was observed, this result was not statistically unambiguous after considering the respective standard deviations. While not all "actives" in a biological assay are amenable to this type of analysis, e.g., due to different mechanisms of action or binding configurations, the ambiguous separation may also be due to employing a single conformer per compound in this study. With that said, there were a subset of biological assays where a clear separation between the NN and NI pairs found. In addition, use of combo Tanimoto (ComboT) alone, independent of superposition optimization type, appears to be the most efficient 3-D score type in identifying these cases.ConclusionThis study provides a statistical guideline for analyzing biological assay data in terms of 3-D similarity and PubChem structure-activity analysis tools. When using a single conformer per compound, a relatively small number of assays appear to be able to separate "active/active" space from "active/inactive" space.
| S-EPMC3223603 | biostudies-literature
Project description:Innovations in LED lighting technology have led to tremendous adoption rates and vastly improved the metrics by which they are traditionally evaluated-including color quality, longevity, and energy efficiency to name a few. Additionally, scientific insight has broadened with respect to the biological impact of light, specifically our circadian rhythm. Indoor electric lighting, despite its many attributes, fails to specifically address the biological responses to light. Traditional electric lighting environments are biologically too dim during the day, too bright at night, and with many people spending much of their lives in these environments, it can lead to circadian dysfunction. The lighting industry's biological solution has been to create bluer days and yellower nights, but the technology created to do so caters primarily to the cones. A better call to action is to provide biologically brighter days and biologically darker nights within the built environment. However, current lighting design practices have specified the comfort and utility of electric light. Brighter intensity during the day can often be uncomfortable or glary, and reduced light intensity at night may compromise visual comfort and safety, both of which will affect user compliance. No single lighting solution will effectively create biologically brighter days and biologically darker nights, but rather a variety of parameters need to be considered. This paper discusses the contributions of spectral power distribution, hue or color temperature, spatial distribution, as well as architectural geometry and surface reflectivity, to achieve biologically relevant lighting.
| S-EPMC8215265 | biostudies-literature