Topics in signal processing: Applications in genomics and genetics
Başlık çevirisi mevcut değil.
- Tez No: 508136
- Danışmanlar: Prof. XIAODONG WANG
- Tez Türü: Doktora
- Konular: Genetik, Genetics
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2016
- Dil: İngilizce
- Üniversite: Columbia University
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 148
Özet
Özet yok.
Özet (Çeviri)
The information in genomic or genetic data is in uenced by various complex processes and appropriate mathematical modeling is required for studying the underlying processes and the data. This dissertation focuses on the formulation of mathematical models for certain problems in genomics and genetics studies and the development of algorithms for proposing ecient solutions. A Bayesian approach for the transcription factor (TF) motif discovery is examined and the extensions are proposed to deal with many interdependent parameters of the TF-DNA binding. The problem is described by statistical terms and a sequential Monte Carlo sampling method is employed for the estimation of unknown parameters. In particular, a class-based resampling approach is applied for the accurate estimation of a set of intrinsic properties of the DNA binding sites. Through statistical analysis of the gene expressions, a motif-based computational approach is developed for the inference of novel regulatory networks in a given bacterial genome. To deal with high false-discovery rates in the genome-wide TF binding predictions, the discriminative learning approaches are examined in the context of sequence classi cation, and a novel mathematical model is introduced to the family of kernel-based Support Vector Machines classi ers. Furthermore, the problem of haplotype phasing is examined based on the genetic data obtained from cost-e ective genotyping technologies. Based on the identi cation and augmentation of a small and relatively more informative genotype set, a sparse dictionary selection algorithm is developed to infer the haplotype pairs for the sampled population. In a relevant context, to detect redundant information in the single nucleotide polymorphism (SNP) sites, the problem of representative (tag) SNP selection is introduced. An information theoretic heuristic is designed for the accurate selection of tag SNPs that capture the genetic diversity in a large sample set from multiple populations. The method is based on a multi-locus mutual information measure, reecting a biological principle in the population genetics that is linkage disequilibrium.
Benzer Tezler
- Görüntü işlemede derin öğrenme tabanlı süper çözünürlük uygulamaları
Deep learning based super resolution applications in image processing
AHENK VURAL
Yüksek Lisans
Türkçe
2021
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiElektronik ve Haberleşme Mühendisliği Ana Bilim Dalı
PROF. DR. ENDER METE EKŞİOĞLU
- Dalgacıklar ve elektrik mühendisliğindeki uygulamaları
Wavelets and application to electrical engineering
EMİNE AYAZ
Yüksek Lisans
Türkçe
1997
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiElektrik Tesisleri Ana Bilim Dalı
PROF. DR. ÖZER ÇİFTÇİOĞLU
- Derin öğrenme tabanlı görevlerin kenar bilişim yöntemiyle uzak sunucuya taşınması
Offloading tasks to remote server for deep learning based applications over edge computing system
HÜSEYİN ENES İLHAN
Yüksek Lisans
Türkçe
2022
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiElektronik ve Haberleşme Mühendisliği Ana Bilim Dalı
PROF. DR. HAKAN ALİ ÇIRPAN
- Beyin bilgisayar arayüzü uygulamalarında motor görüntüleme EEG sinyallerinin analizi için yeni yaklaşımlar
New approaches to analysis of motor imagery EEG signals in brain computer interface applications
ESRA KAYA
Doktora
Türkçe
2022
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve KontrolSelçuk ÜniversitesiElektrik-Elektronik Mühendisliği Ana Bilim Dalı
PROF. DR. İSMAİL SARITAŞ
- Düşük bir hızlarında konuşma kodlama ve uygulamaları
Low bit rate speech coding and applications
TARIK AŞKIN
Doktora
Türkçe
1999
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiPROF.DR. GÜNSEL DURUSOY