Studies showed that single nucleotide variations that alter the protein sequence, structure and function are associated with many diseases in humans. However, the current rate of manually annotating reported nsSNPs cannot catch up with the rate of producing new sequencing data. To aid this process, automated computational approaches are being developed and applied on the unknown data. In this study, we propose a new methodology to collect and organize the information related to the effects of nsSNPs at the amino acid sequence level from various biological databases and to utilize this information in a supervised machine-learning based system to predict the function disrupting capacities of mutations with unknown consequences.

Date: 30.01.2020 / 14:00 Place: A-212

Sorafenib is one of FDA approved targeted agents in HCC treatment. PI3K/AKT pathway is altered in 50% of hepatoma, hence understanding how Sorafenib and PI3K/AKT pathway inhibitors act at signalling level is crucial for targeted therapies and to reveal their off-target effects. In this work, we use gene expression profiles of HCC cells treated with seven different drugs/inhibitors and combination. Our aim is to reveal the important targets and modulators in a drug treatment by inferring the dysregulation of Interactome. In other words, we search for the mechanism of action of drugs in a network context beyond gene list.

Date: 13.01.2020 / 14:00 Place: A-108

This thesis consists of three eye tracking applications. Main purpose of the applications is to develop a communication system for users by tracking eye movements.

Date: 14.01.2020 / 16:00 Place: A-212

This study is about using a persuasive game as a tool to raise awareness about trolling behavior. A game about online trolling behavior is designed and implemented. After exploring how the toxic behaviors that are considered as trolling in the context of online gaming are perceived, this study observes if the persuasive game has an influence in raising awareness and knowledge about these behaviors.

Date: 09.12.2019 / 10:00 Place: A-212

Features extracted from speech are widely used for problems such as biometric speaker identification, but the use of speech data raises concerns about privacy. We propose a method for speech and posture classification using only breath data. The acoustical information was extracted from breath instances using the Hilbert-Huang transform and fed into our CNN-RNN network for classification. We also created our publicly available dataset, BreathBase, which contains more than 5000 breath instances of 20 participants in 5 different postures with 4 different microphones. Using this data, 85% speaker classification and 98% posture classification accuracy is obtained.

Date: 27.11.2019 / 15.00 Place: A-212

There is a high demand for realistic computer aided imagery by many applicatiion areas such as games and movies. Due to the complicated characteristics of certain natural phenomena such as fire, smoke or mist, it is difficult to realistically mimic these effects. There are various approximation methods to visually synthesize lifelike 3D artifacts. The use of flow fields to guide the motion of particles creates a random but natural-looking effect. The aim of this study is to use flow fields to generate realistic 3D visual effects.

Date: 06.12.2019 / 13:00 Place: B-116

In this study, firstly, the effect of kinemorphs on F-formation shapes are investigated by focusing on the differences between the virtual environment and the real life settings. Secondly, the role of one-to-one F-formation shapes on joining a dyadic interaction as a third interactant is also studied.

Date: 12.09.2019 / 15:00 Place: A-212

Our project brings together the concept of sound generation from free text input. Because a good story text can describe an environment quite well, both in terms of visual and aural aspects, we decided to use this feature to create virtual soundscapes that will both be generated procedurally and have the depth, complexity and control of a story text. In this thesis we describe the mechanics of analyzing free text user input queries and a way of converting this analysis into procedural soundscape generation.

Date: 05.09.2019 / 10:00 Place: A-108

In this study we implement a tool that compiles the combinatory categorial grammar rules to extract type-raising rules out of verb categories’ arguments and use them to test it out on natural language corpora like Eve.

Date: 05.09.2019 / 15:00 Place: S-06 (Conference Hall - 2)

Image based CAPTCHA systems are being used to validate if the candidate user is a human or a bot. Several DNN based systems have been achieved to fail this validation process. As a result, the reliability of CAPTCHA has become controversial. Adversarial image is a sample that is intentionally modified by adding non-random noise to deceive DNNs, and recently has been used to deceive DNNs to make CAPTCHA system more reliable. But the adversarial process degrades the image quality which makes it also difficult for humans to classify images and recognize objects. The proposed method preserves perceptual quality of adversarial images and still generates adversarial images which have 100% attack accuracy.

Date: 02.09.2019 / 10:00 Place: A-212