Dynamics of Streptococcus pneumoniae Serotypes Causing Acute Otitis Media Isolated from Children with Spontaneous Middle-Ear Drainage over a 12-Year Period (1999–2010) in a Region of Northern Spain

10 p.

Classification of neocortical interneurons using affinity propagation

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Arrantza sektorea: Santi Burgoa sl, 2018rako plan estrategikoa

Gradu Amaierako Lan hau egiterakoan arrantza sektorearen gaineko jakintza maila handiagotzea, sektorearen egoeraren berri ematea eta graduan zehar ikasgai ezberdinetan landutakoa praktikara eraman eta enpresa bati Plan Estrategikoa lantzea dira nire helburuak. Horretarako lehenik eta behin, Gradua Amaierako Lan honetan erabiliko dudan metodologia azaldu, landuko ditudan atalen buruzko Marko Teorikoa aurkeztu, arrantza sektoreari buruzko ezaugarri, iraganeko eta gaur egungo egoera, jasandako aldaketen zergatik, eta hobetzeko asmoz aurrera eraman daitezkeen pausuak plazaratuko ditut. Ondoren enpresaren kasuan murgilduko naiz, bere historia, xedea, bisioa eta balioak azalduz ondoren analisi estrategikoa egin eta helburuak planteatzeko. Azkenik, Gradu Amaierako Lan honen ondoriekin amaituko da lana.