2009-2010 Master Class - Massimo La Rosa (Trombone)

https://spiral.lynn.edu/conservatory_masterclasses/1092/thumbnail.jp

"A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS: AN APPLICATION TO REVERSE ENGINEERING GENE REGULATORY NETWORK"

The huge amount of biological data has spread the development of plenty of bionformatics tools, databases and web services. In order to face a computational biology problem, there not exist only a way, but different methodologies and strategies, with their own pros and cons, can be applied. In this PhD thesis I present a knowledge-based expert system that aims at helping a bionformatics researcher in the choice of the proper strategy and heuristic in order to resolve a bioinformatics issue. The Knowledge Base of the system is structured by means of an ontology and codes the expertise about the application domain. KB is organized into decision-making modules that introduce a set of metareasoning levels. The proposed expert system is the core reasoning component of BORIS (Bionformatics Organized Resources - an Intelligent System) framework, a research project High Performance Computing and Networking Institute of National Research Council (ICAR-CNR). BORIS, based on a hybrid architecture, can be seen as a crossover between Decision Support System and Workflow Management System because it not only provides decision support, but it help the User in the proper configuration and running of algorithms, tools and services implementing the suggested strategies and, at the same time, builds a workflow that traces both the decision-making activity and the execution of tasks and tools. The whole system will be applied to an actual case study: the reverse engineering of Gene Regulatory Network

Evaluating The Potential Energy Savings Of An Urban Green Infrastructure Through Environmental Simulation

Green infrastructure is a very important aspect to be considered in designing and preparing cities to adapt and mitigate climate change impacts on the built environment. Green based solutions have a strong impact on many aspects, such as controlling storm-water, reducing urban heat island effect, stabilizing soils, facing earthquakes, etcetera. In this paper an environmental analysis is performed by simulation with TRNSYS Studio tool. The cooling potential that can be obtained by trees in residential compounds is assessed, considering shadowing effect, changes in air movement, sky view factor reduction and other simulation-parameter changes. Results show that a reduction of 30 to 50% in cooling demand can be obtained by using a raw of trees on South, East and especially West façades. Two types of trees are tested, showing different cooling performances depending on the height and form of the trees

GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data

Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq data is identifying the cell types within tissue to estimate the quantitative composition of cell populations. Due to the massive amount of available scRNA-seq data, automatic classification approaches for cell typing, based on the most recent deep learning technology, are needed. Here, we present the gene ontology-driven wide and deep learning (GOWDL) model for classifying cell types in several tissues. GOWDL implements a hybrid architecture that considers the functional annotations found in Gene Ontology and the marker genes typical of specific cell types. We performed cross-validation and independent external testing, comparing our algorithm with 12 other state-of-the-art predictors. Classification scores demonstrated that GOWDL reached the best results over five different tissues, except for recall, where we got about 92% versus 97% of the best tool. Finally, we presented a case study on classifying immune cell populations in breast cancer using a hierarchical approach based on GOWDL

Green Infrastructure to reduce cooling loads and heat stress in Mediterranean Climates

Climate change impact on cities and urban warming due to anthropogenic effects are urgent problems to be solved. Among the most beneficious strategies to reduce those impacts we can account the development of green infrastructures in cities, a kind of intervention that assure both mitigation of global warming by reducing greenhouse gases emissions, and adaptation to warmer urban environments. This work presents a building simulation and machine learning methodology to estimate the energy and comfort-related benefits that can be obtained by using a green infrastructure to shadow buildings' façades and roofs. We used previously developed simulation models to test the energy savings provided by different types of trees planted to produce shadows on buildings. Then, we tested different algorithms to predict using a machine learning approach the saving that can be obtained in different buildings-trees contexts for the cities of Catania, Rome, Santiago de Chile and Viña del Mar. Results show that the saving obtained is in the range 5-60%, mainly depending on the number of façade shadowed and on the specie of trees; and the prediction accuracy of machine learning process is over 90% for a binary classification (energy saving > 15% or <15%

Ambienti digitali per lo sviluppo delle competenze trasversali nella didattica universitaria

Digital Environments for the Development of Transversal Competences in University EducationInternational studies show that university teaching is making increasing use of digital environments to integrate traditional teaching. In this paper we consider the contribution that can be made by online environments to develop students’ positive and proactive attitudes with respect to the academic curriculum in order to reduce student drop-out, encourage greater regularity in their academic career, develop transversal competences and promote student guidance. In particular, we have observed the online activities in academic year 2013/2014 carried on by students of General Didactics, a degree course in the Department of Educational Sciences of «Roma Tre» University. These activities include the realization of two online practical classes: completion of the QSA (Questionnaire for Learning Strategies); participation in a cooperative online learning exercise. In both experiences we analyzed the procedures and outcomes. We observed that, through the QSA, students reflected on their learning strategies and on the importance of planning their university commitments: a positive factor is the high percentage of students who took the exam successfully in the first session (approximately 68%). In addition, the questionnaire data clearly show that students found that group work helps to develop cognitive and meta-cognitive competences as well as relationship competences. In particular, we found that in the General Didactics examination the students who had experienced cooperative learning obtained higher grades, on average, than those who did not, and that the former group had less «sigma» compared to the latter

Acceptance of non-invasive computed tomography coronary angiography: for a patient-friendly medicine

PURPOSE: This study was done to evaluate the psychological state and anxiety of patients undergoing computed tomography coronary angiography (CTCA), and assess their acceptance and satisfaction compared to invasive conventional coronary angiography (CCA). MATERIALS AND METHODS: A total of 442 consecutive patients (282 male; mean age 57.7 ± 9.5 years) who underwent CTCA for suspected or known coronary artery disease were evaluated with the Endler Multimodality Anxiety Scales (EMAS) before and after the scan, and a questionnaire administered after the scan. Among the 442 patients, 181 had a history of CCA. Two radiologists assessed the image quality of CTCA. RESULTS: Anxiety was more intense prior to the scan (EMAS score 51.7 vs. 46.7, p < 0.01) and in patients with a history of CCA (EMAS score 55.5 vs. 49.1, p < 0.01). Women presented more intense anxiety (EMAS score 59.5 vs. 47.3, p < 0.01), higher mean heart rate (63.5 ± 7.6 vs. 60.7 ± 7.3 beats per minute, p < 0.01) and a lower image quality than men (p < 0.0001). CTCA proved to be more acceptable than CCA because of accurate preparation, lower concern prior to the examination, negligible pain, higher comfort, and greater overall satisfaction (p < 0.0001). CONCLUSIONS: Computed tomography coronary angiography is a patient-friendly imaging method because of the minimal perceived discomfort. Anxiety may affect CTCA image quality in women

Transcriptomic Analyses Reveal 2 and 4 Family Members of Cytochromes P450 (CYP) Involved in LPS Inflammatory Response in Pharynx of Ciona robusta

Cytochromes P450 (CYP) are enzymes responsible for the biotransformation of most en- dogenous and exogenous agents. The expression of each CYP is influenced by a unique combination of mechanisms and factors including genetic polymorphisms, induction by xenobiotics, and regula- tion by cytokines and hormones. In recent years, Ciona robusta, one of the closest living relatives of vertebrates, has become a model in various fields of biology, in particular for studying inflammatory response. Using an in vivo LPS exposure strategy, next-generation sequencing (NGS) and qRT-PCR combined with bioinformatics and in silico analyses, compared whole pharynx transcripts from naïve and LPS-exposed C. robusta, and we provide the first view of cytochrome genes expression and miRNA regulation in the inflammatory response induced by LPS in a hematopoietic organ. In C. robusta, cytochromes belonging to 2B,2C, 2J, 2U, 4B and 4F subfamilies were deregulated and miRNA network interactions suggest that different conserved and species-specific miRNAs are involved in post-transcriptional regulation of cytochrome genes and that there could be an interplay between specific miRNAs regulating both inflammation and cytochrome molecules in the inflammatory response in C. robusta

Chemical On/Off Switching of Mechanically Planar Chirality and Chiral Anion Recognition in a [2]Rotaxane Molecular Shuttle

We exploit a reversible acid-base triggered molecular shuttling process to switch an appropriately designed rotaxane between prochiral and mechanically planar chiral forms. The mechanically planar enantiomers and their interconversion, arising from ring shuttling, have been characterized by NMR spectroscopy. We also show that the supramolecular interaction of the positively charged rotaxane with optically active anions causes an imbalance in the population of the two enantiomeric co-conformations. This result represents an unprecedented example of chiral molecular recognition and can disclose innovative approaches to enantioselective sensing and catalysis