University of Nebraska Omaha

About: University of Nebraska Omaha is a education organization based out in Omaha, Nebraska, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 4526 authors who have published 8905 publications receiving 213914 citations. The organization is also known as: UNO & University of Omaha.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis

Abstract: Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base-base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel-Ziv techniques from data compression.

Principles for effective virtual teamwork

Abstract: OrganizatiOns tOday Often establish OperatiOns and strategic alliances across the globe, making virtual teamwork critical to their success.5 Many government and military organizations face new challenges, such as combating terrorism, that are better tackled by nimble, well-informed teams than by large hierarchical bureaucracies. In the wake of global expansion and outsourcing, other organizations seek to cut the cost and hassle of bringing team members to a single location. Virtual teams are becoming ubiquitous (Figure 1). Intel Corporation recently conducted a study which revealed that approximately two-thirds of their employees collaborated with team members located at different sites and in different regions. Therefore, it is important to understand how to make virtual teams effective. Virtual teams face new challenges that make them more difficult to manage than traditional face-to-face teams (see Table 1). For example, approximately half of the employees in the study above worked with team members whose work processes and collaboration technologies differed from their own. Virtual teams may struggle to establish cohesive relationships necessary for achieving their objectives. Virtual team members also face competing demands for their attention from their virtual team and from their immediate workplace, and from the practical challenges of assimilating new technologies into their daily routines. Over the past decade of working with virtual teams, we have derived a set of principles for effective virtual teamwork (Table 2). These principles are derived from field experience with hundreds of virtual teams in government, military and business organizations and from extensive laboratory studies. Two assumptions underlie these principles. First, we assume that the collaboration is interpersonal which implies that the virtual team consists of a welldefined group of individuals brought together to produce a specific deliverable such as a software specification, a strategic plan, or a budget proposal. This is referred to as “closed” collaboration by Pisano and Verganti and is distinguished from community-based collaboration which is open to the public. Second, we assume that the technology employed by the virtual teams is reliable and secure. Technological glitches will cripple the productivity of even the most knowledgeable and motivated virtual teams. Our principles are intended to help designers, managers, and virtual team members improve the effectiveness of their virtual teams.

Data mining via multiple criteria linear programming: applications in credit card portfolio management

Abstract: Data mining becomes a cutting-edge information technology tool in today's competitive business world. It helps the company discover previously unknown, valid, and actionable information from various and large databases for crucial business decisions. This paper provides a promising approach of data mining to classify the credit cardholders' behavior through multiple criteria linear programming. After reviewing the history of linear discriminant analyses, we will describe first a model for classifying two-group (e.g. bad or good) credit cardholder behaviors, and then a three-group (e.g. bad, normal, or good) credit model. Besides the discussion of the modeling structure, we will utilize the well-known commercial software package SAS to implement this technology by using a real-life credit card data warehouse. A number of potential business and financial applications will be finally summarized.

Sub-10 nm Gate Length Graphene Transistors: Operating at Terahertz Frequencies with Current Saturation

Abstract: Sub-10 nm Gate Length Graphene Transistors: Operating at Terahertz Frequencies with Current Saturation