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Articles 1 - 10 of 10
Full-Text Articles in Other Computer Sciences
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Doctoral Dissertations
Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …
Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra
Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra
University of New Orleans Theses and Dissertations
Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on …
Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker
Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to …
High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami
High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami
LSU Doctoral Dissertations
Genome sequencing technology has witnessed tremendous progress in terms of throughput and cost per base pair, resulting in an explosion in the size of data. Typical de Bruijn graph-based assembly tools demand a lot of processing power and memory and cannot assemble big datasets unless running on a scaled-up server with terabytes of RAMs or scaled-out cluster with several dozens of nodes. In the first part of this work, we present a distributed next-generation sequence (NGS) assembler called Lazer, that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the …
Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim
Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim
Open Educational Resources
This material introduces Linux File System structures and demonstrates how to use commands to communicate with the operating system through a Terminal program. Basic program structures and system() function of Perl are discussed. A brief introduction to gene-sequencing terminology and file formats are given.
Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim
Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim
Open Educational Resources
This material introduces the AWS console interface, describes how to create an instance on AWS with the VMI provided, connect to that machine instance using the SSH protocol. Once connected, it requires the students to write a script to enter the data folder, which includes gene-sequencing input files and print the first five line of each file remotely. The same exercise can be applied if the VMI is installed on a local machine using virtualization software (e.g. Oracle VirtualBox). In this case, the Terminal program of the VMI can be used to do the exercise.
Designing Computational Biology Workflows With Perl - Part 2, Esma Yildirim
Designing Computational Biology Workflows With Perl - Part 2, Esma Yildirim
Open Educational Resources
This material introduces the AWS console interface, describes how to create an instance on AWS with the VMI provided and connect to that machine instance using the SSH protocol. Once connected, it requires the students to write a script to automate the tasks to create VCF files from two different sample genomes belonging to E.coli microorganisms by using the FASTA and FASTQ files in the input folder of the virtual machine. The same exercise can be applied if the VMI is installed on a local machine using virtualization software (e.g. Oracle VirtualBox). In this case, the Terminal program of the …
Designing Computational Biology Workflows With Perl - Part 2, Esma Yildirim
Designing Computational Biology Workflows With Perl - Part 2, Esma Yildirim
Open Educational Resources
This material briefly reintroduces the DNA double Helix structure, explains SNP and INDEL mutations in genes and describes FASTA, FASTQ, BAM and VCF file formats. It also explains the index creation, alignment, sorting, marking duplicates and variant calling steps of a simple preprocessing workflow and how to write a Perl script to automate the execution of these steps on a Virtual Machine Image.
Designing Computational Biology Workflows With Perl - Part 1 & 2, Esma Yildirim
Designing Computational Biology Workflows With Perl - Part 1 & 2, Esma Yildirim
Open Educational Resources
This manual guides the instructor to combine the partial files of the virtual machine image and construct sequencer.ova file. It is accompanied by the partial files of the virtual machine image.
Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr
Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr
Human–Wildlife Interactions
In this study, we examined the use of an unmanned aerial system (UAS) to monitor fish-eating birds on catfish (Ictalurus spp.) aquaculture facilities in Mississippi, USA. We tested 2 automated computer algorithms to identify bird species using mosaicked imagery taken from a UAS platform. One algorithm identified birds based on color alone (color segmentation), and the other algorithm used shape recognition (template matching), and the results of each algorithm were compared directly to manual counts of the same imagery. We captured digital imagery of great egrets (Ardea alba), great blue herons (A. herodias), …