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SPRINGS: Prediction of Protein- Protein Interaction Sites Using Artificial Neural Networks
TLDR
A novel method SPRINGS (Sequence-based predictor of Protein- protein Interacting Sites) for identification of interaction sites based on sequences is proposed, which uses protein evolutionary information, averaged cumulative hydropathy and predicted relative solvent accessibility from amino acid chains in artificial neural network architecture.
Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation
Question Generation (QG) is fundamentally a simple syntactic transformation; however, many aspects of semantics influence what questions are good to form. We implement this observation by developing
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
TLDR
GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics, is introduced and the description of the data for the 2021 shared task at the associated GEM Workshop is described.
Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questions
TLDR
This work proposes a novel method of generating discriminative questions using a simple rule based system which can take advantage of any question generation system without requiring annotated data of clarification questions.
Genetic Regulation of Phenotypic Plasticity and Canalisation in Yeast Growth
TLDR
This work used a previously published dataset of a biparental yeast population grown in 34 diverse environments and mapped genetic loci regulating variation in phenotypic plasticity, plasticity QTL, and compared them with environment-specific QTL to comprehensively understand the genotype-phenotype map.
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
TLDR
The efficacy of NL-Augmenter is demonstrated by using several of its tranformations to analyze the robustness of popular natural language models and the infrastructure, datacards and robutstness analysis results are shown.
Document categorization using semantic relatedness & Anaphora resolution: A discussion
TLDR
This work develops a general measure to estimate the semantic closeness of documents by utilizing the semantic relatedness of the most discriminative individual words that define the document.
Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits
TLDR
It is demonstrated that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation and improve the ability to predict disease predisposition and identify specific therapeutic targets.
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
TLDR
A framework based on this idea which is able to generate controlled perturbations and identify subsets in text-to-scalar, text- to-text, or data-To-text settings is developed and applied to the GEM generation benchmark.
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