Word Sense Disambiguation with LSTM: Do We Really Need 100 Billion Words?

Recently, Yuan et al. (2016) have shown the effectiveness of using Long Short-Term Memory (LSTM) for performing Word Sense Disambiguation (WSD). Their proposed technique outperformed the previous state-of-the-art with several benchmarks, but neither the training data nor the source code was released. This paper presents the results of a reproduction study of this technique using only openly available datasets (GigaWord, SemCore, OMSTI) and software (TensorFlow). From them, it emerged that state-of-the-art results can be obtained with much less data than hinted by Yuan et al. All code and trained models are made freely available

A diffusion-translocation model for gradient sensing by chemotactic cells

Small chemotactic cells like Dictyostelium and neutrophils transduce shallow spatial chemoattractant gradients into strongly localized intracellular responses. We show that the capacity of a second messenger to establish and maintain localized signals, is mainly determined by its dispersion range, lambda = the square root of D(m)/k(-1), which must be small compared to the cell's length. Therefore, short-living second messengers (high k(-1)) with diffusion coefficients D(m) in the range of 0-5 microm(2) s(-1) are most suitable. Additional to short dispersion ranges, gradient sensing may include positive feedback mechanisms that lead to local activation and global inhibition of second-messenger production. To introduce the essential nonlinear amplification, we have investigated models in which one or more components of the signal transduction cascade translocate from the cytosol to the second messenger in the plasma membrane. A one-component model is able to amplify a 1.5-fold difference of receptor activity over the cell length into a 15-fold difference of second-messenger concentration. Amplification can be improved considerably by introducing an additional activating component that translocates to the membrane. In both models, communication between the front and the back of the cell is mediated by partial depletion of cytosolic components, which leads to both local activation and global inhibition. The results suggest that a biochemically simple and general mechanism may explain various signal localization phenomena not only in chemotactic cells but also those occurring in morphogenesis and cell differentiation

ReferenceNet: a semantic-pragmatic network for capturing reference relations

In this paper, we present ReferenceNet: a semantic-pragmatic network of reference relations between synsets. Synonyms are assumed to be exchangeable in similar contexts and also word embeddings are based on sharing of local contexts represented as vectors. Co-referring words, however, tend to occur in the same topical context but in different local contexts. In addition, they may express different concepts related through topical coherence, and through author framing and perspective. In this paper, we describe how reference relations can be added to WordNet and how they can be acquired. We evaluate two methods of extracting event coreference relations using WordNet relations against a manual annotation of 38 documents within the same topical domain of gun violence. We conclude that precision is reasonable but recall is lower because the Word-Net hierarchy does not sufficiently capture the required coherence and perspective relations

Inferring Drosophila gap gene regulatory network: a parameter sensitivity and perturbation analysis

<p>Abstract</p> <p>Background</p> <p>Inverse modelling of gene regulatory networks (GRNs) capable of simulating continuous spatio-temporal biological processes requires accurate data and a good description of the system. If quantitative relations between genes cannot be extracted from direct measurements, an efficient method to estimate the unknown parameters is mandatory. A model that has been proposed to simulate spatio-temporal gene expression patterns is the connectionist model. This method describes the quantitative dynamics of a regulatory network in space. The model parameters are estimated by means of model-fitting algorithms. The gene interactions are identified without making any prior assumptions concerning the network connectivity. As a result, the inverse modelling might lead to multiple circuits showing the same quantitative behaviour and it is not possible to identify one optimal circuit. Consequently, it is important to address the quality of the circuits in terms of model robustness.</p> <p>Results</p> <p>Here we investigate the sensitivity and robustness of circuits obtained from reverse engineering a model capable of simulating measured gene expression patterns. As a case study we use the early gap gene segmentation mechanism in <it>Drosophila melanogaster</it>. We consider the limitations of the connectionist model used to describe GRN Inferred from spatio-temporal gene expression. We address the problem of circuit discrimination, where the selection criterion within the optimization technique is based of the least square minimization on the error between data and simulated results.</p> <p>Conclusion</p> <p>Parameter sensitivity analysis allows one to discriminate between circuits having significant parameter and qualitative differences but exhibiting the same quantitative pattern. Furthermore, we show that using a stochastic model derived from a deterministic solution, one can introduce fluctuations within the model to analyze the circuits' robustness. Ultimately, we show that there is a close relation between circuit sensitivity and robustness to fluctuation, and that circuit robustness is rather modular than global. The current study shows that reverse engineering of GRNs should not only focus on estimating parameters by minimizing the difference between observation and simulation but also on other model properties. Our study suggests that multi-objective optimization based on robustness and sensitivity analysis has to be considered.</p

Inferring Drosophila gap gene regulatory network: pattern analysis of simulated gene expression profiles and stability analysis

<p>Abstract</p> <p>Background</p> <p>Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any <it>a priori </it>assumptions about the interactions, which all simulate the observed patterns. It is important to analyze the properties of the circuits.</p> <p>Findings</p> <p>We have analyzed the simulated gene expression patterns of previously obtained circuits that describe gap gene dynamics during early <it>Drosophila melanogaster </it>embryogenesis. Using hierarchical clustering we show that amplitude variation and defects observed in the simulated gene expression patterns are linked to similar circuits, which can be grouped. Furthermore, analysis of the long-term dynamics revealed four main dynamical attractors comprising stable patterns and oscillatory patterns. In addition, we also performed a correlation analysis on the parameters showing an intricate correlation pattern.</p> <p>Conclusions</p> <p>The analysis demonstrates that the obtained gap gene circuits are not unique showing variable long-term dynamics and highly correlating scattered parameters. Furthermore, although the model can simulate the pattern up to gastrulation and confirms several of the known regulatory interactions, it does not reproduce the transient expression of all gap genes as observed experimentally. We suggest that the shortcomings of the model may be caused by overfitting, incomplete model description and/or missing data.</p

Large-scale Cross-lingual Language Resources for Referencing and Framing

In this article, we lay out the basic ideas and principles of the project Framing Situations in the Dutch Language. We provide our first results of data acquisition, together with the first data release. We introduce the notion of cross-lingual referential corpora. These corpora consist of texts that make reference to exactly the same incidents. The referential grounding allows us to analyze the framing of these incidents in different languages and across different texts. During the project, we will use the automatically generated data to study linguistic framing as a phenomenon, build framing resources such as lexicons and corpora. We expect to capture larger variation in framing compared to traditional approaches for building such resources. Our first data release, which contains structured data about a large number of incidents and reference texts, can be found at http://dutchframenet. nl/data-releases/

A cell-based model of Nematostella vectensis gastrulation including bottle cell formation, invagination and zippering

AbstractThe gastrulation of Nematostella vectensis, the starlet sea anemone, is morphologically simple yet involves many conserved cell behaviors such as apical constriction, invagination, bottle cell formation, cell migration and zippering found during gastrulation in a wide range of more morphologically complex animals.In this article we study Nematostella gastrulation using a combination of morphometrics and computational modeling. Through this analysis we frame gastrulation as a non-trivial problem, in which two distinct cell domains must change shape to match each other geometrically, while maintaining the integrity of the embryo. Using a detailed cell-based model capable of representing arbitrary cell-shapes such as bottle cells, as well as filopodia, localized adhesion and constriction, we are able to simulate gastrulation and associate emergent macroscopic changes in embryo shape to individual cell behaviors.We have developed a number of testable hypotheses based on the model. First, we hypothesize that the blastomeres need to be stiffer at their apical ends, relative to the rest of the cell perimeter, in order to be able to hold their wedge shape and the dimensions of the blastula, regardless of whether the blastula is sealed or leaky. We also postulate that bottle cells are a consequence of cell strain and low cell–cell adhesion, and can be produced within an epithelium even without apical constriction. Finally, we postulate that apical constriction, filopodia and de-epithelialization are necessary and sufficient for gastrulation based on parameter variation studies

Towards reference-aware FrameNet representations:Bridging generic and specific event knowledge

FrameNet (Baker et al., 2003) is a resource that encodes conceptual and linguistic knowledge in the form of frames: information packages defining word senses and semantic roles associated with a particular type of event, situation or concept. FrameNet is a rich resource for describing how events and situations can be conceptualized in language in different ways, but is limited by its focus on lexical semantics and lack of a notion of reference: a frame-semantic analysis of the event descriptions in (1) would tell us that both describe the same event type (i.e., a commercial transaction, conceptualized from two different perspectives), but not whether they in fact describe the same event token in the real world. (1) a. Yesterday, John sold Mary a book. b. A woman bought a novel in the shop. To address this limitation, we are currently developing a new FrameNet-based resource, comprising a lexical database, annotated corpus and a semantic parser, that is ‘referentially enriched’ in two ways: frame annotations are linked, on one hand, to referential information from an ontology of real-world event tokens, and on the other hand to truth-conditional meaning representations