A graph-based semantic similarity measure for the gene ontology

Existing methods for calculating semantic similarities between pairs of Gene Ontology (GO) terms and gene products often rely on external databases like Gene Ontology Annotation (GOA) that annotate gene products using the GO terms. This dependency leads to some limitations in real applications. Here, we present a semantic similarity algorithm (SSA), that relies exclusively on the GO. When calculating the semantic similarity between a pair of input GO terms, SSA takes into account the shortest path between them, the depth of their nearest common ancestor, and a novel similarity score calculated between the definitions of the involved GO terms. In our work, we use SSA to calculate semantic similarities between pairs of proteins by combining pairwise semantic similarities between the GO terms that annotate the involved proteins. The reliability of SSA was evaluated by comparing the resulting semantic similarities between proteins with the functional similarities between proteins derived from expert annotations or sequence similarity. Comparisons with existing state-of-the-art methods showed that SSA is highly competitive with the other methods. SSA provides a reliable measure for semantics similarity independent of external databases of functional-annotation observations.     

Gene ontology based transfer learning for protein subcellular localization

Background  

Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology.     

An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology

Background  

Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs). They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO). Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity.     

Noninvasive techniques for measuring body elemental composition

In the past 20 yr, in vivo analysis of body elements by neutron activation has become an important tool in medical research. In particular, it provides a much needed means to make quantitative assessments of body composition of human beings in vivo. The data are useful both for basic physiological understanding and for diagnosis and management of a variety of diseases and disorders. This paper traces the development of the in vivo neutron activation technique from basic systems to the present state of the art facilities. A scan of some of the numerous clinical applications that have been made with this technique reveals the broad potentialities of in vivo neutron activation. The paper also considers alternative routes of future development and raises some of the questions now faced in making the technique more widely available to both medical practitioners and medical investigtors. In vivo neutron activation has opened a new era of both clinical diagnosis and therapy evaluation, and investigation into the modeling of body composition. The techniques are new, but it is already clear that considerable strides can be made in increasing accuracy and precision, increasing the number of elements susceptible to measurement, and reducing the dose required for the measurement.     

Software for genome mapping by fingerprinting techniques

A genome mapping package has been developed for reading andassembling data from clones analysed by restriction enzyme fragmentationand polyacrylamide gel electrophoresis. The package comprises:data entry; matching; assembly; statistical analysis; modelling.Data entry can be either manual or by a semiautomatic systembased on a scanning densitometer. The primary emphasis in theanalytical routines is on flexibility and interactive convenience,so that the operator has full knowledge of and control overthe growing map, but a variety of automatic options are included.The package continually grows to meet the needs of the Caenorhabditisproject. Received on July 17, 1987; accepted on November 20, 1987     

Practical techniques for mapping small patches of mangroves

Practical mapping methods employing GPS field surveys and manual image analyses with affordable software were used to assess two mangrove sites in Aklan Province, NE Panay Island, central Philippines. The Jawili mangroves, absent from current maps, actually included 21.5 ha with 24 true mangrove species. On the other hand, the Batan Estuary mangroves, shown to be 4244 ha in available topographic maps, revealed only 406 ha of scattered patches. Actual mangrove data on specific areas worldwide is limited, especially in the Philippines where available maps show discrepancies from actual mangrove distribution. Remote sensing (RS) techniques provide promising results but require expensive setup, particularly for small areas. Therefore, financially limited users need affordable and rapid mapping alternatives. The practical techniques presented here can be immediately implemented at minimal cost and can produce useful estimates of actual mangrove area, fundamental for coastal management. Basic principles used here also have potential applications in other systems and locations. When resources are available though, additional confirmation and precise mapping are also further recommended.     

Comparison of techniques for measuring plasmid stability in yeasts

Summary Three techniques for measuring plasmid stability in yeasts are described and evaluated. The yeast used was aKluyveromyces lactis strain which was transformed with a plasmid, pCR1, to enable production of heterologous α-amylase. The techniques were based on plate counts on a selective antibiotic-containing medium and a non-selective medium, and on clearing zones on starch-supplemented plates for α-amylase detection. The plate ratio and clearing zones methods gave comparable results while the transfer colony method estimated much lower plasmid stabilities.     

A comparison of two techniques for measuring and crossdating tree rings

Crossdating is the core principle of dendrochronology. Our study compared two techniques for measuring and crossdating tree rings using Juniperus virginiana L. (eastern redcedar) as a case study. We used a pseudo 2 × 2 study design comparing the traditional skeleton plot/sliding measuring stage technique to a semi-automatic image analysis program across two technicians. Crossdating was evaluated in COFECHA. Raw measurements of total, earlywood, and latewood widths from the two methods were analyzed using the Verify for Windows program, ANOVA, and correlation matrices. Total ring width and earlywood width were well correlated between techniques and technicians but questionable ring boundaries from image analysis program should be checked under a stereoscope. Juniperus virginiana latewood widths were significantly different between techniques and technicians; therefore, we do not recommend combining latewood measurements from species with limited latewood variability for dendrochronological analysis. A standard definition of the earlywood-latewood boundary that can be replicated across technicians is needed to combine latewood measurements from the sliding measuring stage and image analysis systems.     

Margin based ontology sparse vector learning algorithm and applied in biology science

In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.     

Cross-validation of techniques for measuring lipid content of bovine oocytes and blastocysts

The main objective was to test and validate a fluorescence approach to quantify lipid content of individual bovine oocytes and blastocysts. For Experiment 1, denuded oocytes were evaluated, as well as in vitro-produced blastocysts in a factorial design: cows versus feedlot heifers; three additives during Days 2.5-7.5 of culture (Control; 10% FCS; 0.3 μM phenazine ethosulfate (PES), an electron acceptor that oxidizes NADPH); and two blastocyst stages (early versus expanded). All blastocysts were graded subjectively for darkness (1 = clear … 4 = dark). In Experiment 2, denuded oocytes were used to measure lipid content in a factorial design of: cows versus heifers and four subjective darkness grades (1 = clear … 4 = dark). To quantify lipids, oocytes and 7.5 d blastocysts were fixed and then stained with 1 μg/mL Nile Red dye in mPBS overnight. A digital photograph of the equatorial part of the oocyte and embryo was taken at 200×, and fluorescence intensity (Arbitrary Fluorescence Units, AFU) was measured with Image Pro software. Reverse images of the same photographs were used to count numbers of cytoplasmic lipid droplets of various sizes (LC). The linear regression equation of LC with AFU in oocytes had an r² = 0.84, and for blastocysts r² = 0.91. The LC and AFU also had similar coefficients of variation from the ANOVA for blastocysts (38 vs 44%, respectively). Treatment differences were of similar magnitude with both procedures: lipid content in oocytes and blastocysts from heifers and cows was similar (P > 0.1); PES reduced lipid accumulation, and FCS increased it relative to the Control for AFU (18.6 vs 46.6 vs 36.9 units, respectively), and LC (1763 vs 4081 vs 3310, respectively; all, P < 0.01). Early blastocysts resulted in more lipid accumulation per unit area than expanded ones based on AFU (41.5 vs 26.6) and LC (3519 vs 2583; both P <0.01). There was a strong relationship (P < 0.01) between subjective oocyte and blastocyst darkness and lipid content. The less labor intensive fluorescence staining was a reliable technique for quantifying lipid droplets in oocytes and blastocysts.     

New techniques for physical mapping of the human genome.

We describe improvements in techniques and strategies used for making maps of the human genome. The methods currently used are changing and evolving rapidly. Today's techniques can produce ordered arrays of DNA fragments and overlapping sets of DNA clones covering extensive genomic regions, but they are relatively slow and tedious. Methods under development will speed the process considerably. New developments include a range of applications of the polymerase chain reaction, enhanced procedures for high resolution in situ hybridization, and improved methods for generating, manipulating, and cloning large DNA fragments. More detailed genetic and physical maps will be useful for finding genes, including those associated with human diseases, long before the complete DNA sequence of the human genome is available.     

Defining and measuring trophic role similarity in food webs using regular equivalence

We present a graph theoretic model of analysing food web structure called regular equivalence. Regular equivalence is a method for partitioning the species in a food web into "isotrophic classes" that play the same structural roles, even if they are not directly consuming the same prey or if they do not share the same predators. We contrast regular equivalence models, in which two species are members of the same trophic group if they have trophic links to the same set of other trophic groups, with structural equivalence models, in which species are equivalent if they are connected to the exact same other species. Here, the regular equivalence approach is applied to two published food webs: (1) a topological web (Malaysian pitcher plant insect food web) and (2) a carbon-flow web (St. Marks, Florida seagrass ecosystem food web). Regular equivalence produced a more satisfactory set of classes than did the structural approach, grouping basal taxa with other basal taxa and not with top predators. Regular equivalence models provide a way to mathematically formalize trophic position, trophic group and trophic niche. These models are part of a family of models that includes structural models used extensively by ecologists now. Regular equivalence models uncover similarities in trophic roles at a higher level of organization than do the structural models. The approach outlined is useful for measuring the trophic roles of species in food web models, measuring similarity in trophic relations of two or more species, comparing food webs over time and across geographic regions, and aggregating taxa into trophic groups that reduce the complexity of ecosystem feeding relations without obscuring network relationships. In addition, we hope the approach will prove useful in predicting the outcome of predator-prey interactions in experimental studies.     

An ontology for landscapes

As ecological data increases in breadth, depth, and complexity, the discipline of ecology is increasingly influenced by information science. While this influence provides many opportunities for ecologists, it also necessitates a change in how we manage and share data, and perhaps more fundamentally, define concepts in ecology. Specifically, the information technology process of automated data integration entirely depends upon consistent concept definition. A common tool used in computer science and engineering to specify meanings, which is both novel and offers significant potential to ecology, is an ontology. An ontology is a formal representation of knowledge in which concepts are described by their meaning and their relationship to each other. Ontologies are a tool that can be used to ‘explicitly specify a concept’ (Gruber, 1993) and this approach is uncommon in ecology. In this paper, we develop an ontology for the concept of ‘landscape’ that captures the most general definitions and usages of this term. We selected the concept of landscape because it is often used in very different ways by investigators and hence generates linguistic uncertainty. A graphic theoretic (i.e., visual) model is provided which describes the set of structuring rules we used to define the relationships between ‘landscape’ and appropriately related terms. Based upon these rules, a landscape necessarily contains a spatial component (i.e., area), structure and function (i.e., ecosystems), and is scale independent. This approach provides the set of necessary conditions for landscape studies to reduce linguistic uncertainty, and facilitate interoperability of data, i.e., in a manner that promotes data linkages and quantitative synthesis particularly by automatic data synthesis programs that are likely to become an important part of ecology in the future. Simply put, we use an ontology, a technique novel to ecology but not other disciplines, to define ‘landscape,’ thereby clearly delineating one subset of its potential general usage. As such this ontology can serve as both a checklist for landscape studies and a blueprint for additional ecological ontologies.