Sökning: "gene regulatory network inference"
Visar resultat 1 - 5 av 8 uppsatser innehållade orden gene regulatory network inference.
1. Autoencoder-Based Likelihood-Free Parameter Inference of Gene Regulatory Network
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Likelihood-free parameter inference is a well-known statistical methodology that estimates the posterior distribution of model parameters even in cases where the likelihood function is intractable. The performance of this method is highly correlated with the learning of summary statistics, which capture the key features from the high dimensional data such as time series. LÄS MER
2. Inferring Gene regulatory networks using Graph Neural Networks
Master-uppsats, KTH/GenteknologiSammanfattning : Inom beräkningsbiologin är det snabbt på väg att bli allt vanligare att ta fram genetiska regleringsnätverk (GRN). På grund av storleken på de undersökta nätverken använder många forskare maskininlärning för att härleda GRN från genuttrycksdata, vanligtvis från RNA-seq. LÄS MER
3. Capturing genes with high impact based on reconstruction errors produced by variational autoencoders
Master-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : In this work we present a novel method to extract potential hub genes, transcription factors and regions with densely interconnected protein-protein-interaction networks from RNAseq data. To achieve this we deploy variational autoencoders, a generative machine learning framework, and extract the gene-wise reconstruction errors. LÄS MER
4. Imputing connections of random gene networks from time series data using ANNs
Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationSammanfattning : This thesis presents the architecture of a convolutional neural network which is trained to impute the connections of randomly generated gene regulatory networks under varying amounts of regularisation. The generated gene networks are simulated from 10 different starting conditions for each set of connections in order to obtain multiple time series. LÄS MER
5. Robust Community Predictions of Hubs in Gene Regulatory Networks
Master-uppsats, Linköpings universitet/BioinformatikSammanfattning : Many diseases, such as cardiovascular diseases, cancer and diabetes, originate from several malfunctions in biological systems. The human body is regulated by a wide range of biological systems, composed of biological entities interacting in complex networks, responsible for carrying out specific functions. LÄS MER