SWIM: A computational tool to unveiling crucial nodes in complex biological networks

SWItchMiner (SWIM) is a wizard-like software implementation of a procedure, previously described, able to extract information contained in complex networks. Specifically, SWIM allows unearthing the existence of a new class of hubs, called "fight-club hubs", characterized by a marked negative correlation with their first nearest neighbors. Among them, a special subset of genes, called "switch genes", appears to be characterized by an unusual pattern of intra- and inter-module connections that confers them a crucial topological role, interestingly mirrored by the evidence of their clinic-biological relevance. Here, we applied SWIM to a large panel of cancer datasets from The Cancer Genome Atlas, in order to highlight switch genes that could be critically associated with the drastic changes in the physiological state of cells or tissues induced by the cancer development. We discovered that switch genes are found in all cancers we studied and they encompass protein coding genes and non-coding RNAs, recovering many known key cancer players but also many new potential biomarkers not yet characterized in cancer context. Furthermore, SWIM is amenable to detect switch genes in different organisms and cell conditions, with the potential to uncover important players in biologically relevant scenarios, including but not limited to human cancer

LUCIA: An open source 3D expressive avatar for multimodal h.m.i.

LUCIA is an MPEG-4 facial animation system developed at ISTC-CNR . It works on standard Facial Animation Parameters and speaks with the Italian version of FESTIVAL TTS. To achieve an emotive/expressive talking head LUCIA was build from real human data physically extracted by ELITE optotracking movement analyzer. LUCIA can copy a real human by reproducing the movements of passive markers positioned on his face and recorded by the ELITE device or can be driven by an emotional XML tagged input text, thus realizing a true audio/visual emotive/expressive synthesis. Synchronization between visual and audio data is very important in order to create the correct WAV and FAP files needed for the animation. LUCIA\u27s voice is based on the ISTC Italian version of FESTIVAL-MBROLA packages, modified by means of an appropriate APML/VSML tagged language. LUCIA is available in two dif-ferent versions: an open source framework and the "work in progress" WebGL

SAD-based Italian Forced Alignment Strategies

Abstract. The Evalita 2011 contest proposed two forced alignment tasks, word and phone segmentation, and two modalities, "open" and "closed". A system for each combination of task and modality has been proposed and submitted for evaluation. Direct use of silence/activity detection in forced alignment has been tested. Positive effects were shown in the acoustic model training step, especially when dealing with long pauses. Exploitation of multiple forced alignment systems through a voting procedure has also been tested

Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer

Extensive molecular characterization of human colorectal cancer (CRC) via Next Generation Sequencing (NGS) indicated that genetic or epigenetic dysregulation of a relevant, but limited, number of molecular pathways typically occurs in this tumor. The molecular picture of the disease is significantly complicated by the frequent occurrence of individually rare genetic aberrations, which expand tumor heterogeneity. Inter- and intratumor molecular heterogeneity is very likely responsible for the remarkable individual variability in the response to conventional and target-driven first-line therapies, in metastatic CRC (mCRC) patients, whose median overall survival remains unsatisfactory. Implementation of an extensive molecular characterization of mCRC in the clinical routine does not yet appear feasible on a large scale, while multigene panel sequencing of most commonly mutated oncogene/oncosuppressor hotspots is more easily achievable. Here, we report that clinical multigene panel sequencing performed for anti-EGFR therapy predictive purposes in 639 formalin-fixed paraffin-embedded (FFPE) mCRC specimens revealed previously unknown pairwise mutation associations and a high proportion of cases carrying actionable gene mutations. Most importantly, a simple principal component analysis directed the delineation of a new molecular stratification of mCRC patients in eight groups characterized by non-random, specific mutational association patterns (MAPs), aggregating samples with similar biology. These data were validated on a The Cancer Genome Atlas (TCGA) CRC dataset. The proposed stratification may provide great opportunities to direct more informed therapeutic decisions in the majority of mCRC cases

Towards long-term social child-robot interaction: using multi-activity switching to engage young users

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI

Mivoq Evalita 2016 PosTwITA tagger

The POS tagger developed by Mivoq to tag tweets according to PosTwITA task guidelines as defined at Evalita 2016 is presented. The system obtained third position with 92.7% of accuracy.Si presenta il POS tagger sviluppato da Mivoq per etichettare i tweet secondo le linee guida del task PosT-wITA, cos come definite per Evalita 2016. Il sistema ha ottenuto la terza posizione con un accuratezza del 92.7%

Tacito abburattato : discorsi politici, e morali

Sign.: [ ]\p4\s, A-K\p12\s, L\p8\s.Anteportada.Portada con doble filete.Portada y cabeceras xilográficas.Texto con reclamos