An enhanced initialization method for non-negative matrix factorization

Non-negative matrix factorization (NMF) is a dimensionality reduction tool, and has been applied to many areas such as bioinformatics, face image classification, etc. However, it often converges to some local optima because of its random initial NMF factors (W and H matrices). To solve this problem, some researchers have paid much attention to the NMF initialization problem. In this paper, we first apply the k-means clustering to initialize the factor W, and then we calculate the initial factor H using four different initialization methods (three standard and one new). The experiments were carried out on the eight real datasets and the results showed that the proposed method (EIn-NMF) achieved less error and faster convergence compared with both random initialization based NMF and the three standard methods for k-means based NMF

Dimension reduction based robust digital ımage watermarking using truncated singular value decomposition and discrete wavelet transform

Telif hakkı koruma, kimlik doğrulama, parmak izi, içerik etiketleme gibi alanlarda kullanılan damgalama tekniklerinde genel olarak sinyal işleme dönüşümleri ve matematiksel teknikler kullanılır. Bu araştırmada çoğu damgalama tekniğinde tercih edilen Tekil Değer Ayrışımı (TDA) yerine, boyut indirgeme tabanlı Kesik-TDA tekniği kullanılmıştır. Önerilen bu teknik Ayrık Dalgacık Dönüşümü (ADD) ile birlikte kullanılmıştır. Temel TDA-ADD tabanlı yönteme göre önerilen yöntemin histogram eşitleme dışında tüm olası saldırılara karşı algılanamazlık ve dayanıklılık performanslarında ilerleme kaydettiği gözlenmiştir. Önerilen şemanın farklı matris ayrışımı ve sinyal işleme dönüşümlerinin kullanıldığı alternatif damgalama şemalarına yön vereceği tahmin edilmektedir.Signal processing transformations and mathematical techniques are generally used in watermarking techniques used in areas such as copyright protection, authentication, fingerprinting, content tagging. In this study, instead of the Singular Value Decomposition (SVD), which is preferred in most watermarking schemes, the dimension reduction-based truncated-SVD technique is used. This technique is combined with the Discrete Wavelet Transform. Compared to the baseline SVD-DWT-based technique, it has been observed that the proposed scheme has made progress in imperceptibility and resistance performances against all possible attacks, except histogram equalization. It is predicted that the proposed scheme will lead to alternative stamping schemes using different matrix decomposition and signal transformations

Integrative clustering by non-negative matrix factorization can reveal coherent functional groups from gene profile data

Recent developments in molecular biology and tech- niques for genome-wide data acquisition have resulted in abun- dance of data to profile genes and predict their function. These data sets may come from diverse sources and it is an open question how to commonly address them and fuse them into a joint prediction model. A prevailing technique to identify groups of related genes that exhibit similar profiles is profile-based clustering. Cluster inference may benefit from consensus across different clustering models. In this paper we propose a technique that develops separate gene clusters from each of available data sources and then fuses them by means of non-negative matrix factorization. We use gene profile data on the budding yeast S. cerevisiae to demonstrate that this approach can successfully integrate heterogeneous data sets and yields high-quality clusters that could otherwise not be inferred by simply merging the gene profiles prior to clustering

Unsupervised Algorithms for Microarray Sample Stratification

The amount of data made available by microarrays gives researchers the opportunity to delve into the complexity of biological systems. However, the noisy and extremely high-dimensional nature of this kind of data poses significant challenges. Microarrays allow for the parallel measurement of thousands of molecular objects spanning different layers of interactions. In order to be able to discover hidden patterns, the most disparate analytical techniques have been proposed. Here, we describe the basic methodologies to approach the analysis of microarray datasets that focus on the task of (sub)group discovery.Peer reviewe

Proceeding seminar ICABS di Malaysia

proceeding seminar internasiona

Geeniekspressiooni andmete integreerimine teiste ‘oomika’ andmetega kirjeldamaks endomeetriumi retseptiivsuse bioloogilisi mehhanisme

Väitekirja elektrooniline versioon ei sisalda publikatsiooneMaailma Terviseorganisatsiooni statistika väidab, et umbes 10% püsisuhetes olevatest naistest on ühel või teisel põhjusel viljatud. Naise viljakust mõjutab välja palju erinevaid faktoreid ning setõttu on viljatuse põhjuste leidmine tihti väga keeruline. Viljatust põhjustavateks faktoriteks võivad olla üldine terviseseisund, erinevad haigused, geneetiline taust, väliskeskkonna ja eluviisiga seotud tegurid. Ühe näitena võib tuua embrüo pesastumist (implantatsioon) emaka limaskesta (endomeetriumi), mis võib toimuda ainult kindla lühikese perioodi vältel (implantatsiooni aken), kui endomeetrium on embrüo suhtes kõige vastuvõtlikum. Implantatsiooni akna periood on aga iga naise jaoks erinev, ning on määratud erinevate bioloogiliste protsesside poolt. Kunstliku viljastamise (IVF) läbiviimise jaoks on kriitiline teada täpset implantatsiooni akna aega, sellega seotud mehhanisme ja nende vastastikust mõju. Selleks, et uurida mehhanismide omavahelisi seoseid, panime paariviisiliselt kokku erinevaid geneetilise regulatsiooni andmekihte, milleks olid RNA, mikroRNA ja DNA metülatsiooni admed, ja mida koos nimetatakse ‘oomika’ andmekihtideks. Kokkuvõtvalt näitavad antud töö tulemused, et, võrreldes ühe ‘oomika’ andmekihi uurimisega, ‘oomika’ andmekihtide kombineerimine aitab paremini mõista endomeetriumi retseptiivsusega seotud bioloogilisi protsesse ning vältida valepositiivseid tulemusi. Antud tööga me rõhutame süsteemibioloogia ning paljude andmekihtide samaaegse kasutamise olulisust naise reproduktiivsuse bioloogiliste mehhanismide uurimisel.According to the World Health Organization, over 10% of females in a stable relationship are suffering from involuntary infertility/subfertility worldwide. Untangling the reasons for this is difficult because female reproduction is a sophisticated matter and can be affected by many factors such as health, accompanying diseases, genetic background, environment, and lifestyle. As a specific example, embryo implantation – its attachment to the uterine lining (endometrium) – occurs only during a relatively short period of time, called the window of implantation (WOI), when the endometrium is most receptive to an embryo. This is critical for a commonly used fertility treatment of in vitro fertilizaton (IVF) – and to make matters more complex, the WOI is not the same for everyone, but adjusted by an interlocking system of biological regulation mechanisms. Thus, to provide successful IVF, it is important to know these exact regulation mechanisms – and, since they interact with one another, to understand how they work together, not just individually. We used pairwise integration of data from different layers of genetic regulation, such as RNA, microRNA, and DNA methylation, called together the ‘omics’ layers, and showed the advantage of the data integration approach over the usage of just a single ‘omics’ layer. As a result, we obtained the lists of novel potential biomarkers that could regulate WOI, validated some previously known receptivity biomarkers, and showed that integration of different ‘omics’ layers helps to avoid false-positive results. With our work, we encourage other researchers in the female reproduction field to integrate several data layers for further studieshttps://www.ester.ee/record=b535138

Immersive analytics for oncology patient cohorts

This thesis proposes a novel interactive immersive analytics tool and methods to interrogate the cancer patient cohort in an immersive virtual environment, namely Virtual Reality to Observe Oncology data Models (VROOM). The overall objective is to develop an immersive analytics platform, which includes a data analytics pipeline from raw gene expression data to immersive visualisation on virtual and augmented reality platforms utilising a game engine. Unity3D has been used to implement the visualisation. Work in this thesis could provide oncologists and clinicians with an interactive visualisation and visual analytics platform that helps them to drive their analysis in treatment efficacy and achieve the goal of evidence-based personalised medicine. The thesis integrates the latest discovery and development in cancer patients’ prognoses, immersive technologies, machine learning, decision support system and interactive visualisation to form an immersive analytics platform of complex genomic data. For this thesis, the experimental paradigm that will be followed is in understanding transcriptomics in cancer samples. This thesis specifically investigates gene expression data to determine the biological similarity revealed by the patient's tumour samples' transcriptomic profiles revealing the active genes in different patients. In summary, the thesis contributes to i) a novel immersive analytics platform for patient cohort data interrogation in similarity space where the similarity space is based on the patient's biological and genomic similarity; ii) an effective immersive environment optimisation design based on the usability study of exocentric and egocentric visualisation, audio and sound design optimisation; iii) an integration of trusted and familiar 2D biomedical visual analytics methods into the immersive environment; iv) novel use of the game theory as the decision-making system engine to help the analytics process, and application of the optimal transport theory in missing data imputation to ensure the preservation of data distribution; and v) case studies to showcase the real-world application of the visualisation and its effectiveness

Toxicogenomics : a transcriptomics approach to assess the toxicity of 4-nitrophenol to sachharomyces cerevisiae

PhD ThesisSince the industrial revolution there has been a significant increase in the production, use and release of man-made chemicals (xenobiotics) into the environment. This is cause for concern because the toxicity of some xenobiotics are unknown, consequently there is an increased need for high throughput sensitive assays that can be used to detect and evaluate the toxicity of xenobiotics. The advent of transcriptomics has provided scientists with a sensitive, accurate high throughput method to measure gene expression in response to chemicals (toxicogenomics). The aim of this work was to investigate the effects of the widely distributed xenobiotic and model organic pollutant, 4-nitrophenol on gene expression in the model eukaryote Saccharomyces cerevisiae. This would assess if this chemical had more subtle effects on cells than previous traditional biochemistry studies revealed and to see if certain genes could be used to develop a specific microarray test to detect the presence of 4-nitrophenol in the environment. Traditional growth inhibition tests were used to ascertain the toxicity of 4-nitrophenol to S. cerevisiae. Traditional tests were used to establish EC10 & EC50 concentrations in standard defined media (SDM). Subsequently S. cerevisiae were exposed to 10 & 39 mg/l 4-nitrophenol in SDM and samples taken for expression profiling when conditions were optimal, one, two and three hours after 4-nitrophenol exposure. qRT-PCR was used to validate the gene expression results. Approximately 600 genes were increased in expression and ˜600 genes were decreased in expression at 10 & 39 4-nitrophenol. Genes associated with RNA processing, ribosome formation, mitochondrial biogenesis, and respiratory activity were differentially expressed. Time series analysis showed 4-nitrophenol caused damage to cell walls and membranes as inferred from increased expression of genes for cell wall and membrane synthesis (DCW1, GRE2). This resulted in hypo-osmotic stress (increased expression of SLN1, & AQY2) and decreased expression of genes involved in cell replication (MDY2, PAN3). At 39 mg/l 4-nitrophenol expression of additional drug resistance genes increased after one (PDR3, PDR15, PDR16), two (PDR3, PDR15) and three (PDR5) hour’s exposure. After two hours cells had respiration deficiencies shown by; increased expression of RIM2 a mitochondrial carrier protein, which rescues respiration deficient cells, and decreased production of mitochondrial oxidoreductases. Fourteen iron homeostasis genes were increased in expression and iron requiring cytochromes and oxidoreductases were decreased in expression alongside glucose transporter encoding genes. The results showed respiration was reduced and implicated an increased requirement for iron. Expression of general Environmental Stress Response (ESR) genes initially decreased (one hour of exposure to 39 mg/l 4-nitrophenol). However, three hours after the addition of 4-nitrophenol expression of ESR genes increased. ESR genes are known to be repressed for up to two hours after chemical exposure, and are known to be involved in respiration. The results in this study show reduced respiration is temporary. Increased expression of genes involved in respiration and growth after three hours show that treated cells have adapted to 4-nitrophenol presence. Only two iron homeostasis genes were increased in expression after three hours exposure to 39 mg/l 4-nitrophenol showing iron concentrations inside the cell have stabilised. Exposure to 4-nitrophenol resulted in hypo-osmotic stress, probably caused by membrane damage. This led to decreased intracellular iron concentrations and increased oxidative stress, iron availability directly controls expression of ESR genes and oxidoreductases and may explain the effects seen on mitochondrial respiratory activity and the general stress response observed. The study confirms biochemical results which have shown 4-nitrophenol damages cell membranes and reduces respiration, and implicates iron deficiency in playing a role in this process. It also shows that at sub lethal concentrations cells can adapt their respiration and growth to survive in the presence of 4-nitrophenol.Natural Environment Research Council (NERC) AstraZeneca COGEME (Manchester University