ANALYSIS AND CONTROL OF ELECTRICAL PROPERTIES OF ORGANIC MATERIALS BASED ON MORPHOLOGICAL AND STRUCTURAL CHARACTERISTICS FOR VARIOUS DEVICE APPLICATIONS

The discovery of electrical properties in organic π-conjugated materials signaled the rise in organic electronics. The delocalized nature of the π-orbitals from resonance stabilization opened new opportunities to design and engineer materials in micro/nano scales. Advantages of organic electronics are that they are transparent, printable, flexible, tunable, biocompatible, and solution processable materials. However, these very advantages also make organic electrical materials less crystalline and ordered compared to inorganic materials, making it challenging to fabricate organic electronics with the high stability and performance of inorganic materials. Hence, many engineering strategies have been implemented to gain control over or an understanding of the packing parameters of small organic molecules when made into solid state devices. Two engineering approaches are widely adopted in this respect: molecular design and blending of different organic molecules. In Chapter 2., we explore how molecular design affects packing parameters of organic molecules by analyzing various material properties of thin films made of pH triggered self-assembling peptide-π-peptide molecules. We report interesting correlations between organic-inorganic hybrid systems where highly conductive electronic conduction pathways were occasionally formed. Based on this, we have found that the interaction between organic and inorganic domains fundamentally affects the electrical and structural properties of the ensuing solid state thin films. It was shown that we can control the structural and electrical properties of the organic-inorganic hybrid systems by altering the peptide side chains as well as the acid/base used to form the inorganic minerals. In chapter 3, an electrically active small organic molecule (α4T) was blended in polystyrene (PS) dielectric matrix. At concentrations of α4T before percolation of the PS thin film, α4T crystals localized charges when charges were injected into dielectrics containing these crystals. The presence of α4T crystals increased dielectric polarization potential of the dielectric, storing charges more stably in the dielectric and increasing the maximum charge storage capacity. At concentrations of α4T above when percolation occurs, doping of α4T crystals by gases were observed electrically in reversible and non-reversible ways. Doping α4T by gases were shown to affect the structural, electrical, and thermodynamic properties of the α4T-PS blended thin films

Active Contour Models

Active contour models have been widely applied to image segmentation and analysis. It has been successfully used in contour detection for object recognition, computer vision, computer graphics, and biomedical image processing such as X-ray, MRI and Ultrasound images. The energy-minimizing active contour models or snakes were developed by Kass, Witkin and Terzopoulos in 1987. Snakes are curves defined in the image domain that can move under the influence of internal forces within the curve itself and external forces derived from the image data. Snakes perform well on certain types of images (such as well-defined, convex shapes). There have been several improvements proposed to the original snake or active contour model. These improvements include balloon snakes, adaptive snakes, and GVF snakes. In this project, I reviewed and implemented their algorithms as well as the original snake model. GCBAC (Graph Cut Based Active Contour) is one of alternative solutions to the object extraction problem. Although the GCBAC belongs to family of active contour models, it differs fundamentally from original active contours. In this project, I also review and implement the GCBAC algorithm as well

Development of an online genome sequence annotation pipeline

Advances in DNA sequencing technology have significantly reduced the costs associated with sequencing an organism's genome. This has led to greater numbers of plant genomes being sequenced. Once sequenced and re-assembled, these genome sequences are annotated to identify genes and other important sequence features. Annotation usually involves computational analysis by a bioinformaticist followed by manual (biologist) curation of the predicted genes. While there are many standalone (command line) pipelines available and many individual web based tools available for annotation, there are no one-stop web sites where the biologist can access several gene prediction tools and have the integrated and optimized results returned to them for manual curation. Several fruit genomes are currently being sequenced (apple, peach, strawberry, citrus and cacao) and the annotations will be made available via the tree fruit genome databases housed at Washington State University. This project focuses on implementing a framework of web-based gene prediction and comparative sequence similarity applications that performs automated sequence annotation including gene structure and function predictions, and enable user based manipulation of the results via the application GenSAS, the Genome Sequence Annotation Server

Addition of a breeding database in the Genome Database for Rosaceae

Breeding programs produce large datasets that require efficient management systems to keep track of performance, pedigree, geographical and image-based data. With the development of DNA-based screening technologies, more breeding programs perform genotyping in addition to phenotyping for performance evaluation. The integration of breeding data with other genomic and genetic data is instrumental for the refinement of marker-assisted breeding tools, enhances genetic understanding of important crop traits and maximizes access and utility by crop breeders and allied scientists. Development of new infrastructure in the Genome Database for Rosaceae (GDR) was designed and implemented to enable secure and efficient storage, management and analysis of large datasets from the Washington State University apple breeding program and subsequently expanded to fit datasets from other Rosaceae breeders. The infrastructure was built using the software Chado and Drupal, making use of the Natural Diversity module to accommodate large-scale phenotypic and genotypic data. Breeders can search accessions within the GDR to identify individuals with specific trait combinations. Results from Search by Parentage lists individuals with parents in common and results from Individual Variety pages link to all data available on each chosen individual including pedigree, phenotypic and genotypic information. Genotypic data are searchable by markers and alleles; results are linked to other pages in the GDR to enable the user to access tools such as GBrowse and CMap. This breeding database provides users with the opportunity to search datasets in a fully targeted manner and retrieve and compare performance data from multiple selections, years and sites, and to output the data needed for variety release publications and patent applications. The breeding database facilitates efficient program management. Storing publicly available breeding data in a database together with genomic and genetic data will further accelerate the cross-utilization of diverse data types by researchers from various disciplines. Database URL: http://www.rosaceae.org/breeders_toolbox

Synteny of Prunus and other model plant species

BACKGROUND: Fragmentary conservation of synteny has been reported between map-anchored Prunus sequences and Arabidopsis. With the availability of genome sequence for fellow rosid I members Populus and Medicago, we analyzed the synteny between Prunus and the three model genomes. Eight Prunus BAC sequences and map-anchored Prunus sequences were used in the comparison. RESULTS: We found a well conserved synteny across the Prunus species – peach, plum, and apricot – and Populus using a set of homologous Prunus BACs. Conversely, we could not detect any synteny with Arabidopsis in this region. Other peach BACs also showed extensive synteny with Populus. The syntenic regions detected were up to 477 kb in Populus. Two syntenic regions between Arabidopsis and these BACs were much shorter, around 10 kb. We also found syntenic regions that are conserved between the Prunus BACs and Medicago. The array of synteny corresponded with the proposed whole genome duplication events in Populus and Medicago. Using map-anchored Prunus sequences, we detected many syntenic blocks with several gene pairs between Prunus and Populus or Arabidopsis. We observed a more complex network of synteny between Prunus-Arabidopsis, indicative of multiple genome duplication and subsequence gene loss in Arabidopsis. CONCLUSION: Our result shows the striking microsynteny between the Prunus BACs and the genome of Populus and Medicago. In macrosynteny analysis, more distinct Prunus regions were syntenic to Populus than to Arabidopsis

Extension modules for storage, visualization and querying of genomic, genetic and breeding data in Tripal databases

Tripal is an open-source database platform primarily used for development of genomic, genetic and breeding databases. We report here on the release of the Chado Loader, Chado Data Display and Chado Search modules to extend the functionality of the core Tripal modules. These new extension modules provide additional tools for (1) data loading, (2) customized visualization and (3) advanced search functions for supported data types such as organism, marker, QTL/Mendelian Trait Loci, germplasm, map, project, phenotype, genotype and their respective metadata. The Chado Loader module provides data collection templates in Excel with defined metadata and data loaders with front end forms. The Chado Data Display module contains tools to visualize each data type and the metadata which can be used as is or customized as desired. The Chado Search module provides search and download functionality for the supported data types. Also included are the tools to visualize map and species summary. The use of materialized views in the Chado Search module enables better performance as well as flexibility of data modeling in Chado, allowing existing Tripal databases with different metadata types to utilize the module. These Tripal Extension modules are implemented in the Genome Database for Rosaceae (rosaceae.org), CottonGen (cottongen.org), Citrus Genome Database (citrusgenomedb.org), Genome Database for Vaccinium (vaccinium.org) and the Cool Season Food Legume Database (coolseasonfoodlegume.org). Database URL : https://www.citrusgenomedb.org/ , https://www.coolseasonfoodlegume.org/ , https://www.cottongen.org/ , https://www.rosaceae.org/ , https://www.vaccinium.org

GDR (Genome Database for Rosaceae): integrated web-database for Rosaceae genomics and genetics data

The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org

Proformer: a hybrid macaron transformer model predicts expression values from promoter sequences

Abstract The breakthrough high-throughput measurement of the cis-regulatory activity of millions of randomly generated promoters provides an unprecedented opportunity to systematically decode the cis-regulatory logic that determines the expression values. We developed an end-to-end transformer encoder architecture named Proformer to predict the expression values from DNA sequences. Proformer used a Macaron-like Transformer encoder architecture, where two half-step feed forward (FFN) layers were placed at the beginning and the end of each encoder block, and a separable 1D convolution layer was inserted after the first FFN layer and in front of the multi-head attention layer. The sliding k-mers from one-hot encoded sequences were mapped onto a continuous embedding, combined with the learned positional embedding and strand embedding (forward strand vs. reverse complemented strand) as the sequence input. Moreover, Proformer introduced multiple expression heads with mask filling to prevent the transformer models from collapsing when training on relatively small amount of data. We empirically determined that this design had significantly better performance than the conventional design such as using the global pooling layer as the output layer for the regression task. These analyses support the notion that Proformer provides a novel method of learning and enhances our understanding of how cis-regulatory sequences determine the expression values