Sökning: "Computational Biology"
Visar resultat 1 - 5 av 44 uppsatser innehållade orden Computational Biology.
1. The production of recombinant 6LZE_A and NS2B-NS3 in E. coli
Master-uppsats, Lunds universitet/Bioteknik (master); Lunds universitet/Bioteknik (CI)Sammanfattning : Even though the first coronavirus pandemic was registered in 1965, SARS-CoV-2 was better acknowledged when it caused the worldwide pandemic in 2019 in which millions of individuals lost their lives. Due to its facile way of spreading from one individual to another, the number of infected cases has gone up to more than 750 million to this day. LÄS MER
2. Computational prediction of cell-cell interactions in the brain-tumour microenvironment
Master-uppsats, Uppsala universitet/Institutionen för biologisk grundutbildningSammanfattning : Glioblastoma is the fastest-growing, and the most common malignant brain tumour in adults. It is normally treated with surgery and radio- or chemotherapy, but the approximate life expectancy is of 15 months with a high probability of cancer recurring. Therefore, there is a need for decreasing its severity. LÄS MER
3. Determining Protein Conformational Ensembles by Combining Machine Learning and SAXS
Master-uppsats, KTH/Tillämpad fysikSammanfattning : In structural biology, immense effort has been put into discovering functionally relevant atomic resolution protein structures. Still, most experimental, computational and machine learning-based methods alone struggle to capture all the functionally relevant states of many proteins without very involved and system-specific techniques. LÄS MER
4. 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
5. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. LÄS MER