Mining biomedical information from scientific literature

The rapid evolution and proliferation of a world-wide computerized network, the Internet, resulted in an overwhelming and constantly growing amount of publicly available data and information, a fact that was also verified in biomedicine. However, the lack of structure of textual data inhibits its direct processing by computational solutions. Information extraction is the task of text mining that intends to automatically collect information from unstructured text data sources. The goal of the work described in this thesis was to build innovative solutions for biomedical information extraction from scientific literature, through the development of simple software artifacts for developers and biocurators, delivering more accurate, usable and faster results. We started by tackling named entity recognition - a crucial initial task - with the development of Gimli, a machine-learning-based solution that follows an incremental approach to optimize extracted linguistic characteristics for each concept type. Afterwards, Totum was built to harmonize concept names provided by heterogeneous systems, delivering a robust solution with improved performance results. Such approach takes advantage of heterogenous corpora to deliver cross-corpus harmonization that is not constrained to specific characteristics. Since previous solutions do not provide links to knowledge bases, Neji was built to streamline the development of complex and custom solutions for biomedical concept name recognition and normalization. This was achieved through a modular and flexible framework focused on speed and performance, integrating a large amount of processing modules optimized for the biomedical domain. To offer on-demand heterogenous biomedical concept identification, we developed BeCAS, a web application, service and widget. We also tackled relation mining by developing TrigNER, a machine-learning-based solution for biomedical event trigger recognition, which applies an automatic algorithm to obtain the best linguistic features and model parameters for each event type. Finally, in order to assist biocurators, Egas was developed to support rapid, interactive and real-time collaborative curation of biomedical documents, through manual and automatic in-line annotation of concepts and relations. Overall, the research work presented in this thesis contributed to a more accurate update of current biomedical knowledge bases, towards improved hypothesis generation and knowledge discovery.

Curricular training report: clinical studies coordination in a clinical research organization vs an investigational site perspective

This report describes my experience of nine months as a trainee of a CRO (Eurotrials, Scientific Consultants), as well as a trainee of a clinical research site (Clinical Academic Center – Braga, Association). This document describes the European framework about clinical research and the Portuguese situation compared to similar countries. The activities developed during this internship are also described. These activities are divided in two phases. The first one occurred in Eurotrials, Scientific Consultants, a CRO specialized in clinical research and scientific advice. The first weeks were dedicated to intensive self-training needed to perform CTA tasks. These tasks included qualification, initiation and monitoring activities related to clinical trials, as well as the development of a quality management system. The second phase took place on 2CA-Braga, a clinical research center located in Hospital of Braga. Clinical studies coordination was the main focus of this second phase of my internship, as well as negotiation of clinical studies agreements. I had also the opportunity to participate in “1as Jornadas de Investigação Clínica e Inovação” (1st Clinical Investigation and Innovation Conference) organized by 2CA-Braga. Globally, this internship was a great opportunity to get knowledge and experience in the implementation and management of clinical trials, in a CRO and clinical research site perspectives. These two perspectives provided an interesting overview about the scientific needs of different players involved in clinical research. To conclude, this internship strengthened the knowledge acquired from my academic background, which make me able to face and overcome new challenges in the clinical research area.