Life Sciences Commons^™

Adversarial Discriminative Domain Adaptation For Extracting Protein-Protein Interactions From Text, Anthony Rios, Ramakanth Kavuluru, Zhiyong Lu

Commonwealth Computational Summit

Relation extraction is the process of extracting structured information from unstructured text. Recently, neural networks (NNs) have produced state-of-art results in extracting protein-protein interactions (PPIs) from text. While multiple corpora have been created to extract PPIs from text, most methods have shown poor cross-corpora generalization. In other words, models trained on one dataset perform poorly on other datasets for the same task. In the case of PPI, the F1 has been shown to vary by as much as 30% between different datasets. In this work, we utilize adversarial discriminative domain adaptation (ADDA) to improve the generalization between the source and …

Aberrant Coordination Geometries Discovered In Most Abundant Metalloproteins, Sen Yao, Robert M. Flight, Eric C. Rouchka, Hunter N. B. Moseley

Commonwealth Computational Summit

Metalloproteins play crucial biochemical roles in our body and are essential across all domains of life. The structural environment around a metal ion, especially the coordination geometry (CG), is both sequentially and functionally relevant. Studies of the metalloprotein’s CG will greatly help alleviate the imbalance between the ample sequence data available and the insufficient knowledge on protein functions. Current methodologies in characterizing metalloproteins’ CG consider only previously reported CG (canonical CG) models based primarily on nonbiological chemical context. Exceptions to these canonical CG models can greatly hamper the ability to characterize metalloproteins both structurally and functionally.

The Use Of Course-Based Research In Computational Analysis Of Genomes To Enhance Student Learning, Christopher Shaffer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

G-Onramp: Create Genome Browsers That Enable Undergraduate Students To Participate In Collaborative Genome Annotations, Wilson Leung, Yating Liu, Luke Sargent, Jeremy Goecks, Sarah C.R. Elgin

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Chromosome Conformation In Context, James Taylor

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Machine Learning Analysis Identifies Drosophila Grunge/Atrophin As An Important Learning And Memory Gene Required For Memory Retention And Social Learning, Balint Kacsoh

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Systems Level Approach To Temporal Expression Dynamics In Drosophila Reveals Clusters Of Long Term Memory Genes, Julianna Bozler, Balint Kacsoh, Giovanni Bosco

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Cage: A Tool For Identifying Genes With Correlated Spatiotemporal Expression, Basheer Becerra

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch

MODVIS Workshop

In the natural world, the past is usually a good guide to the future. If light from the sun and sky is blue earlier in the day and yellow now, then it is likely to be more yellow later, as the sun's elevation decreases. But is the light reflected from a scene into the eye as predictable as the light incident upon the scene, especially when lighting changes are not just spectral but include changes in local shadows and mutual reflections? The aim of this work was to test the predictability of cone photoreceptor signals in the wild over the …

Software Development For Genome Sequence Analysis, David Farr

Symposium Of University Research and Creative Expression (SOURCE)

The cost of genome sequencing has decreased rapidly, expanding availability for many biological applications (Muir 2016). For example, researchers can now obtain genome sequences from multiple populations under different types of selection. Comparison of these sequences allows for identification of chromosome regions and specific genes associated with adaptive evolution (Kelly 2013). As an increasing number of researchers engage in this type of inquiry, many have created in-house computer scripts to analyze the raw sequence data (e.g., Kelly 2013), creating a gap in both continuity and standardization.

Using a test dataset and preliminary results from an ongoing artificial selection experiment in …

Analysis Of Hiv-1 Quasispecies Sequences Generated By High Throughput Sequencing (Hts) Using Hive, Naila Gulzar, Bhavna Hora, Konstantinos Karagiannis, Krista Smith, Feng Gao, Raja Mazumder

GW Research Days 2016 - 2020

The high level of genetic variability of Human Immunodeficiency Virus type 1 (HIV-1) is caused by the low fidelity of its replication machinery. This leads to evolution of swarm-like viral populations often described as quasispecies. High throughput sequencing (HTS) technology provides higher resolution over Sanger sequencing, enabling detection of low frequency variant genomes. However, quasispecies analysis is still a challenge due to the systematic noise, introduced by HTS technology. This leads to the increase in type I errors (also known as false positives) and the underlying genetic diversity, which can lead to mathematically insolvable type II errors (also known as …

Mutations In Braf Are Associated With Higher Levels Of Immune Infiltrates In Microsatellite-Stable Colon Cancer, Jake Rubin, Eduard Porta Parto

GW Research Days 2016 - 2020

While BRAF is among the most well-established oncogenes in human cancers, more recently it has garnered attention for its role in suppressing antitumor immunity, especially in melanoma. Because tumor-infiltrating lymphocyte (TIL) density is strongly prognostic in colorectal cancer (CRC)⁷, we decided to investigate the connection between TIL density and the BRAF-activating V600E mutation in CRC.

We used ESTIMATE to quantify immune infiltrate in samples from the TCGA colon adenocarcinoma (COAD) dataset (n = 216). This is an algorithm that uses the gene-expression signature of 141 immune-related genes to infer the presence of immune cells in the tumor infiltrate. …

P08. Unravelling Organelle Genome Evolution Architecture Using Rna-Sequencing Data, Matheus Sanita Lima, David Roy Smith

Western Research Forum

Background: Mitochondria genomes vary from 11 Mb to 6 kb, while plastids can vary from 1 Mb to 30 kb. Non-coding DNA accounts for most of this size variation, but the mechanistic and evolutionary reasons for that are still unknown. Next generation sequencing has generated unprecedented amounts of genomic and transcriptomic data that can be used for organelle genome evolution studies. However, most of these data is used only for the study of cell nucleus. Therefore, I decided to use these untapped data source to investigate the transcription of organelle genomes in plastid-bearing protists.

Methods: I mapped the transcriptomes over …

A Network Mdoel To Investigate Robustness Of Gene Expressions, Naresh Pasupuleti

UNO Student Research and Creative Activity Fair

Correlation networks are ideal to describe the relationship between the expression profiles of genes. Gene expression is a characteristic exhibited by a particular gene. Our body has thousands of genes; each of them expresses differently, and each one of them has a particular function associated with them. When genes corresponding to a particular part of the body becomes non-functional, i.e., not expressed, then the function corresponding to that part of the body does not happen, thereby causing impairment or mutations. Co-regulation is a method involved in clustering analysis to find genes that perform similar functions. We want to identify genes …

Identification Of Optimal Parameter Ranges In Building And Assessing Correlation Networks Built From Gene Expression., Qianran Li

UNO Student Research and Creative Activity Fair

In this project, I investigate and define the range of acceptable outputs of a gene expression correlation network model. Gene expression refers to the amount of product made by a gene under a given biological condition. A correlation network is a graphical model where the nodes represent genes in an organism and the edges represent the amount of correlation between genes, based on their expression. Correlation network modeling has been used in cellular and biomedical domains to identify functional relationships between genes. The network model in general is a wonderful tool for showcasing relationships, but often times they are misused …