Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Experimental and numerical studies of hybrid PCM embedded in plastering mortar for enhanced thermal behaviour of buildings

This paper proposes a methodology for improvement of energy efficiency in buildings through the innovative simultaneous incorporation of three distinct phase change materials (here termed as hybrid PCM) in plastering mortars for façade walls. The thermal performance of a hybrid PCM mortar was experimentally evaluated by comparing the behaviour of a prototype test cell (including hybrid PCM plastering mortar) subjected to realistic daily temperature profiles, with the behaviour of a similar prototype test cell, in which no PCM was added. A numerical simulation model was employed (using ANSYS-FLUENT) to validate the capacity of simulating temperature evolution within the prototype containing hybrid PCM, as well as to understand the contribution of hybrid PCM to energy efficiency. Incorporation of hybrid PCM into plastering mortars was found to have the potential to significantly reduce heating/cooling temperature demands for maintaining the interior temperature within comfort levels when compared to normal mortars (without PCM), or even mortars comprising a single type of PCM.

In vitro and in vivo studies of temozolomide loading in zeolite structures as drug delivery systems for glioblastoma

Zeolites Y (faujasite) and MOR (mordonite) were used as hosts for temozolomide (TMZ), a current good-standard chemotherapeutic agent used in the treatment of glioblastoma brain tumors. TMZ was loaded into zeolites by liquid-phase adsorption at controlled pH. FTIR, 1H NMR, MS, SEM, UV/vis and chemical analysis demonstrated the successful loading of TMZ into zeolite hosts. The hydrolysis of TMZ in MTIC (TMZ metabolite) after the preparation of drug delivery systems (DDS) was observed in simulated body fluid. The effect of zeolites and DDS were evaluated on the viability of glioblastoma cell lines. Unloaded Y zeolite presented toxicity to cancer cells in contrast to MOR. In accordance, the best results in potentiation of the TMZ effect was obtained with MOR. We found that mordonite loaded with 0.026 mmol of TMZ was able to decrease the half maximal inhibitory concentrations (IC50) at least 3-fold in comparison to free temozolomide both in vitro and in vivo.