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Gene expression Partial Correlation in chromosome 4 COPD patients
Author: Michele Gentili.

Chronic obstructive pulmonary disease (COPD) is a complex disease influenced by environmental exposures (most notably, cigarette smoking) and genetic factors. Genome-wide association studies have identified thousands of genomic regions associated with complex diseases. The chromosome 4q region harbors multiple genetic risk loci for chronic obstructive pulmonary disease (COPD). To determine whether genes in this region are part of a gene expression network, we studied lung tissue RNA-Seq from COPD cases and controls.  

Design of a New Topological Approach for the Prediction of Protein-Protein Interactions
Author: Leonardo Martini, Sapienza University of Rome

Protein-Protein Interactions (PPIs) play an essential role in several biological processes. In many cases, proteins perform essential functions by interacting to constitute protein complexes. Identifying new Protein-Protein interactions is thus crucial in understanding cells' biological mechanisms.

Generation of complete realistic cellular network traffic

Charging Data Records are acknowledged as a standard tool for studying human mobility, infrastructure usage, and traffic behavior. We name such datasets as CdRs to distinguish them from the traditional Call Detail Records (CDRs), describing call and SMS cellular communication only. CdRs describe time-stamped and geo-referenced event types (i.e., data, calls, SMS) generated by each mobile device interacting with operator networks.

Algorithms for Characterizing the Spreading of Misinformation on Social Networks through the Lens of Temporal Networks.

Social networks enable us to stay in contact with people all over the world, and to read news related to events that occur over the globe in almost real-time. While this has many positive impacts, such as allowing the report of adverse events. Unfortunately, such speed of diffusion of information over social networks has also important negative implications. In many cases malicious users may try to take advantage of the structure of social networks to spread misinformation.

The role of Telegram's mediums during protests in Belarus 2020
The role of Telegram's mediums during protests in Belarus 2020
Authors: Ivan Slobojhan; Rajesh Sharma (University of Tartu)

More and more anti-government protests have occurred in the world in recent years. A common denominator for such protests is that they all rely on social media.

(Mis)leading the COVID-19 vaccination discourse on Twitter

An exploratory study of infodemic around the pandemic

Authors: Shakshi Sharma, Rajesh Sharma (University of Tartu, Estonia)

The ongoing discourse in social media has amplified the fears, uncertainties, and doubts (FUD) surrounding COVID-19 and the currently available vaccines, leading to an infodemic (a portmanteau of information and epidemic, referring to the spread of potentially accurate and inaccurate information about a disease spreading like an epidemic).

Detecting Misinformation on YouTube Videos
Detecting Misinformation on YouTube Videos
Authors: Shakshi Sharma (University of Tartu, Estonia) Rajesh Sharma (University of Tartu, Estonia)

In present times, Online Social Media (OSM) platforms such as Facebook, YouTube, and Twitter, have been used by billions of individuals for establishing a narrative, conducting propaganda, and disseminating misinformation.

DEAP-FAKED
DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection
Authors: Shakshi Sharma (University of Tartu, Estonia); Rajesh Sharma (University of Tartu, Estonia)

Fake News on social media platforms has received a lot of attention in recent years, notably for incidents relating to politics (the 2016 US Presidential election) and healthcare (the COVID-19 infodemic, to name a few). Several approaches for identifying fake news have been presented in the literature. The methodologies range from network analysis techniques to Natural Language Processing (NLP) and the use of Graph Neural Networks (GNNs).