PURPOSE DNA repair capacity (DRC) is a determinant not only of cancer development but also of individual response to therapy. Previously, altered base and nucleotide excision repair (BER and NER) have been described in lymphocytes of patients with sporadic colorectal cancer. We, for the first time, evaluate both excision repair capacities in human colon biopsies to study their participation in ...

This paper explains for the Arabic language, how to extract named entities and topics from news articles. Due to the lack of high quality tools for Named Entity Recognition (NER) and topic identification for Arabic, we have built an Arabic NER (RenA) and an Arabic topic extraction tool using the popular LDA algorithm (ALDA). NER involves extracting information and identifying types, such as nam...

In recent years, many researchers have leveraged structural information from dependency trees to improve Named Entity Recognition (NER). Most of their methods take dependency-tree labels as input features for NER model training. However, such is not inherently provided in most corpora, making the with low usability practice. To effectively exploit potential word-dependency knowledge, motivated ...

So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka. nested), and discontinuous NER, which have mostly studied individually. Recently, a growing interest built for unified tackling the above jobs concurrently one single model. Current best-performing methods mainly include span-based sequence-to-sequence models, where unfortunately fo...

Accessibility within chromatin is an important factor in the prompt removal of UV-induced DNA damage by nucleotide excision repair (NER). Chromatin remodeling by the SWI/SNF complex has been shown to play an important modulating role in NER in vitro and yeast in vivo. Nevertheless, the molecular basis of cross-talk between SWI/SNF and NER in mammalian cells is not fully understood. Here, we sho...

Named Entity Recognition (NER) in biomedical literature is a very active research area. NER is a crucial component of biomedical text mining because it allows for information retrieval, reasoning and knowledge discovery. Much research has been carried out in this area using semantic type categories, such as “DNA”, “RNA”, “proteins” and “genes”. However, disease NER has not received its needed a...

The capacity of tumor cells for nucleotide excision repair (NER) is a major determinant of the efficacy of and resistance to DNA-damaging chemotherapeutics, such as cisplatin. Here, we demonstrate that using lesion-specific monoclonal antibodies, NER capacity is enhanced in human lung cancer cells after preconditioning with DNA-damaging agents. Preconditioning of cells with a nonlethal dose of ...

Support vector machine (SVM) is one of the popular machine learning techniques used in various text processing tasks including named entity recognition (NER). The performance of the SVM classifier largely depends on the appropriateness of the kernel function. In the last few years a number of task-specific kernel functions have been proposed and used in various text processing tasks, for exampl...

Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is nowadays considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali usi...

In general, stochastic tumors show genomic instability associated with the proliferation of DNA point mutations, that is, a mutator phenotype. This feature cannot be explained by a dysfunctional mismatch repair alone, and indicates that nucleotide excision repair (NER) and/or base excision repair should be suppressed. However, mutations in NER genes are not causally implicated in the oncogenesi...