We present a new approach for pathogens and gene product normalization in the biomedical literature. The idea of this approach was motivated by needs such as literature curation, in particular applied to the field of infectious diseases thus, variants of bacterial species (S. aureus, Staphyloccocus aureus, ...) and their gene products (protein ArsC, Arsenical pump modifier, Arsenate reductase, ...

In recent years, the number of published biomedical articles has increased as researchers have focused on biological domains to investigate the functions of biological objects, such as genes and proteins. However, the ambiguous nature of genes and their products have rendered the literature more complex for readers and curators of molecular interaction databases. To address this challenge, a no...

In this paper we present an approach to score aggregation for specialized search systems. In our work we focus on document ranking in scientific publication databases. We work with the collection of scientific publications of the CERN Document Server. This paper reports on work in progress and describes rank aggregation framework with score normalization. We present results that we obtained wit...

LocalMotif uses a combination of three different scoring functions which individually describe three different characteristics of a motif. The relative entropy score (RES) measures the degree of surprise in the motif nucleotide pattern with respect to the background distribution of nucleotides. The over-representation score (ORS) measures the overabundance of the number of instances of the moti...

In this paper, we describe and compare systems for text normalization based on statistical machine translation (SMT) methods which are constructed with the support of internet users. Internet users normalize text displayed in a web interface, thereby providing a parallel corpus of normalized and nonnormalized text. With this corpus, SMT models are generated to translate non-normalized into norm...

In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space a...

MicroRNAs (miRNAs) are short, endogenous non-coding RNAs that function as guide molecules to regulate transcription of their target messenger RNAs. Several methods including low-density qPCR arrays are being increasingly used to profile the expression of these molecules in a variety of different biological conditions. Reliable analysis of expression profiles demands removal of technical variati...

Diseases play central roles in many areas of biomedical research and healthcare. Consequently, aggregating the disease knowledge and treatment research reports becomes an extremely critical issue, especially in rapid-growth knowledge bases (e.g. PubMed). We therefore developed a system, AuDis, for disease mention recognition and normalization in biomedical texts. Our system utilizes an order tw...

In recent years, various neural network architectures have been successfully applied to natural language processing (NLP) tasks such as named entity normalization. Named normalization is a fundamental task for extracting information in free text, which aims map mentions text gold standard entities given domain-specific ontology; however, the biomedical domain still challenging because of multip...

User authentication system using a smart card or authentication token is drawing more and more attention. The limitation of the size of the RAM inside the processor for user authentication necessitates a verification algorithm with the efficient usage of the memory. In this paper, we present a score normalization method, which is suitable for embedded speaker verification system. Proposed score...