Computational Biology Commons^™

Deep Models For Brain Em Image Segmentation: Novel Insights And Improved Performance, Ahmed Fakhry, Hanchuan Peng, Shuiwang Ji

Computer Science Faculty Publications

Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation.

Results: In this work, we proposed a novel design of DNNs for …

Isquest: Finding Insertion Sequences In Prokaryotic Sequence Fragment Data, Abhishek Biswas, David T. Gauthier, Desh Ranjan, Mohammad Zubair

Computer Science Faculty Publications

Motivation: Insertion sequences (ISs) are transposable elements present in most bacterial and archaeal genomes that play an important role in genomic evolution. The increasing availability of sequenced prokaryotic genomes offers the opportunity to study ISs comprehensively, but development of efficient and accurate tools is required for discovery and annotation. Additionally, prokaryotic genomes are frequently deposited as incomplete, or draft stage because of the substantial cost and effort required to finish genome assembly projects. Development of methods to identify IS directly from raw sequence reads or draft genomes are therefore desirable. Software tools such as Optimized Annotation System for Insertion Sequences …

Ether Bridge Formation And Chemical Diversification In Loline Alkaloid Biosynthesis, Juan Pan

Theses and Dissertations--Plant Pathology

Loline alkaloids, found in many grass-Epichloë symbiota, are toxic or feeding deterrent to invertebrates. The loline alkaloids all share a saturated pyrrolizidine ring with a 1-amine group and an ether bridge linking C2 and C7. The steps in biosynthesis of loline alkaloids are catalyzed by enzymes encoded by a gene cluster, designated LOL, in the Epichloë genome. This dissertation addresses the enzymatic, genetic and evolutionary basis for diversification of these alkaloids, focusing on ether bridge formation and the subsequent modifications of the 1-amine to form different loline alkaloids.

Through gene complementation of a natural lolO mutant and comparison …

Physiologically-Based Pharmacokinetic Modeling For Predicting Caffeine/Theophylline-Ciprofloxacin Interactions, David M. Ng, Ali Navid

STAR Program Research Presentations

Dynamics of interactions between the drugs caffeine, theophylline, and ciprofloxacin are predicted using physiologically-based pharmacokinetic (PBPK) modeling. Pharmacokinetic means the model determines where the drugs are distributed in the body over time. Physiologically-based means the anatomy and physiology of the human body are reflected in the structure and functioning of the model. Multiple drugs can interact to increase or decrease their beneficial and/or undesired effects. This is important because some common substances, such as caffeine in coffee, soft drinks, and energy drinks, are actually drugs that affect the body. Ciprofloxacin is an inhibitor of caffeine and theophylline metabolism; such inhibition …

How Long Is A Piece Of Loop?, Yoonjoo Choi, Sumeet Agarwal, Charlotte M. Deane

Dartmouth Scholarship

Loops are irregular structures which connect two secondary structure elements in proteins. They often play important roles in function, including enzyme reactions and ligand binding. Despite their importance, their structure remains difficult to predict. Most protein loop structure prediction methods sample local loop segments and score them. In particular protein loop classifications and database search methods depend heavily on local properties of loops. Here we examine the distance between a loop's end points (span). We find that the distribution of loop span appears to be independent of the number of residues in the loop, in other words the separation between …

Physiologically-Based Pharmacokinetic Modeling Of Acetaminophen Metabolism And Toxicity, David M. Ng, Ali Navid

STAR Program Research Presentations

Acetaminophen is a common analgesic and antipyretic. Metabolism of acetaminophen and acetaminophen-induced liver necrosis are predicted using physiologically-based pharmacokinetic (PBPK) modeling. Pharmacokinetic means the model determines where the drug is distributed in the body over time. Physiologically-based means the anatomy and physiology of the human body is reflected in the structure and functioning of the model. Acetaminophen is usually safe and effective when taken as recommended, but consumption at higher levels may lead to liver damage. Additionally, other factors such as alcoholic liver disease, smoking, and malnutrition affect the maximum safe dose of acetaminophen.

Mtbindingsim: Simulate Protein Binding To Microtubules, Julia T. Philip, Charles H. Pence, Holly V. Goodson

Faculty Publications

Summary: Many protein–protein interactions are more complex than can be accounted for by 1:1 binding models. However, biochemists have few tools available to help them recognize and predict the behaviors of these more complicated systems, making it difficult to design experiments that distinguish between possible binding models. MTBindingSim provides researchers with an environment in which they can rapidly compare different models of binding for a given scenario. It is written specifically with microtubule polymers in mind, but many of its models apply equally well to any polymer or any protein–protein interaction. MTBindingSim can thus both help in training intuition about …

Planning Combinatorial Disulfide Cross-Links For Protein Fold Determination, Fei Xiong, Alan M Friedman, Chris Bailey-Kellogg

Dartmouth Scholarship

Fold recognition techniques take advantage of the limited number of overall structural organizations, and have become increasingly effective at identifying the fold of a given target sequence. However, in the absence of sufficient sequence identity, it remains difficult for fold recognition methods to always select the correct model. While a native-like model is often among a pool of highly ranked models, it is not necessarily the highest-ranked one, and the model rankings depend sensitively on the scoring function used. Structure elucidation methods can then be employed to decide among the models based on relatively rapid biochemical/biophysical experiments.

Physiologically-Based Pharmacokinetic Modeling For Predicting Drug-Drug Interactions, David M. Ng, Ali Navid

STAR Program Research Presentations

Dynamics of interactions between the drugs caffeine and ciprofloxacin are predicted using physiologically-based pharmacokinetic (PBPK) modeling. Pharmacokinetic means the model determines where the drugs are distributed in the body over time. Physiologically-based means the anatomy and physiology of the human body is reflected in the structure and functioning of the model. Multiple drugs can interact to increase or decrease their beneficial and/or undesired effects. This is important because some common substances, such as caffeine in coffee and soft drinks, are actually drugs that affect the body. By implementing the model as a computer program, it is relatively straightforward to perform …

Computational Network Analysis Of The Anatomical And Genetic Organizations In The Mouse Brain, Shuiwang Ji

Computer Science Faculty Publications

Motivation: The mammalian central nervous system (CNS) generates high-level behavior and cognitive functions. Elucidating the anatomical and genetic organizations in the CNS is a key step toward understanding the functional brain circuitry. The CNS contains an enormous number of cell types, each with unique gene expression patterns. Therefore, it is of central importance to capture the spatial expression patterns in the brain. Currently, genome-wide atlas of spatial expression patterns in the mouse brain has been made available, and the data are in the form of aligned 3D data arrays. The sheer volume and complexity of these data pose significant challenges …

Ab Initio Exon Definition Using An Information Theory-Based Approach, Peter K. Rogan

Biochemistry Publications

Transcribed exons in genes are joined together at donor and acceptor splice sites precisely and efficiently to generate mRNAs capa ble of being translated into proteins. The sequence variability in individual splice sites can be modeled using Shannon information theory. In the laboratory, the degree of individual splice site use is inferred from the structures of mRNAs and their relative abundance. These structures can be predicted using a bipartite information theory framework that is guided by current knowledge of biological mechanisms for exon recognition. We present the results of this analysis for the complete dataset of all expressed human exons.

Letter From The Dean, Lalit Verma

Discovery, The Student Journal of Dale Bumpers College of Agricultural, Food and Life Sciences

No abstract provided.

Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.

Mathematics & Statistics Faculty Publications

Background: Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates.

Results: Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained …