Pregled bibliografske jedinice broj: 1119422
Microbe Detection Using Deep Learning
Microbe Detection Using Deep Learning, 2020., diplomski rad, diplomski, Fakultet elektrotehnike i računarstva, Zagreb
CROSBI ID: 1119422 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Microbe Detection Using Deep Learning
Autori
Baksa, Mirna
Vrsta, podvrsta i kategorija rada
Ocjenski radovi, diplomski rad, diplomski
Fakultet
Fakultet elektrotehnike i računarstva
Mjesto
Zagreb
Datum
16.09
Godina
2020
Stranica
67
Mentor
Šikić, Mile
Ključne riječi
bioinformatics, deep learning, triplet loss, autoencoder, classification
Sažetak
Microbes, omnipresent microorganisms invisible to the naked eye, impact many functions in the human body. The ability to detect and classify them is essential in order to discover diseases, prescribe medication, and keep a healthy lifestyle. The goal of this thesis is to develop a method for microbe detection based on a deep learning architecture. The architecture is designed to find suitable representations of signals corresponding to sequenced microbe DNA fragments. After finding the signal repre sentations, an appropriate distance metric is used to separate different species in the latent space. In the end, reads are classified using a suitable classifier.
Izvorni jezik
Engleski
POVEZANOST RADA
Projekti:
HRZZ-IP-2018-01-5886 - De novo sastavljanje genoma i metagenoma (SIGMA) (Šikić, Mile, HRZZ ) ( CroRIS)
Profili:
Mile Šikić
(mentor)