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The Edinburgh Parallel Computing Centre (EPCC) is a leading research center located at the University of Edinburgh in Scotland. Established in 1998, EPCC specializes in high-performance computing (HPC), parallel computing, and data-intensive research. It serves as a hub for collaboration between academic researchers and industry partners, promoting the advancement of computational techniques and technologies.

Enthought is a software company known for its focus on scientific computing, data analysis, and visualization. Founded in 2001, Enthought provides tools, libraries, and services primarily aimed at researchers, scientists, and engineers. One of its most notable offerings is the Enthought Python Distribution (EPD), which includes a comprehensive collection of Python libraries for scientific computing and data analysis, such as NumPy, SciPy, and Matplotlib.

The Finite-Difference Time-Domain (FDTD) method is a computational algorithm used to solve differential equations that describe how electromagnetic waves propagate through a medium. This technique is particularly effective for simulating wave phenomena in complex geometries and material structures. ### Key Features of FDTD: 1. **Time Domain Approach**: FDTD is a time-domain approach, meaning it computes the electromagnetic fields (electric and magnetic) as functions of both time and space.

The Future Orientation Index (FOI) is a concept often used in social sciences, particularly psychology and developmental studies, to assess how individuals or groups perceive and plan for the future. It reflects the extent to which people are oriented towards long-term goals and the degree to which they consider future consequences of their actions. Key components of the Future Orientation Index may include: 1. **Goal Setting**: The ability to establish and pursue long-term objectives.

A General Circulation Model (GCM) is a complex mathematical model used to simulate and understand the Earth's climate system, including atmospheric and oceanic processes. GCMs are fundamental tools in climate science, enabling researchers to study weather patterns, climate change, and the interaction of various components of the Earth's system.

Genomatix is a bioinformatics company that specializes in providing software solutions and services for the analysis of genomic data. Founded in the late 1990s, Genomatix focuses on interpreting complex biological data, particularly in the fields of genomics, transcriptomics, and epigenomics. Their tools are designed to assist researchers in understanding gene regulation, discovering biomarkers, and analyzing high-throughput sequencing data.

Guided analytics refers to a data analytics approach that provides users with structured paths or workflows to explore and analyze data. This method often incorporates various visual aids, recommendations, and step-by-step navigation that help users, particularly those with less technical expertise, to derive insights from data effectively. Guided analytics aims to make the data analysis process more intuitive and accessible.

HH-suite is a software tool designed for sensitive sequence searching and protein homology detection. It is particularly focused on finding homologous sequences in large databases using HMM-HMM (Hidden Markov Model - Hidden Markov Model) comparisons. HH-suite builds on the principles of HMMER and allows for the comparison of sequences to HMMs derived from multiple sequence alignments, enabling the identification of distant homologs that might not be detected by traditional sequence alignment methods.

HMMER is a bioinformatics software suite designed for searching and aligning sequence data using Hidden Markov Models (HMMs). It is particularly useful for protein sequence analysis and for identifying homologous sequences in large databases. Here are some key features of HMMER: 1. **Hidden Markov Models**: HMMER uses HMMs, which are statistical models that can represent the sequences and structural information present in biological sequences.

The history of numerical weather prediction (NWP) is a fascinating journey that intertwines advancements in mathematics, computing, and meteorology. Below is a summary of its evolution: ### Early Concepts (1900s-1940s) - **Mathematical Foundations**: The theoretical groundwork for numerical weather prediction began in the early 20th century with advancements in partial differential equations and fluid dynamics, which are essential for modeling atmospheric processes.

HyCOM, or Hybrid Coordinate Ocean Model, is a type of oceanographic numerical model designed to simulate ocean circulation and dynamics. It utilizes a hybrid coordinate system that combines aspects of both Cartesian (grid-based) and sigma (depth) coordinates, allowing for more accurate representation of ocean processes across varying depths and regions. HyCOM is particularly useful for studying ocean currents, temperature distribution, sea surface height, and other key oceanographic variables.

In silico clinical trials refer to the use of computer simulations and computational models to conduct clinical trials, as opposed to traditional, in vivo (live organisms) trials or in vitro (test tube) studies. These digital simulations can replicate biological processes and predict the effects of medical interventions, therapies, or drugs within a virtual environment.

In silico medicine refers to the application of computational methods and models to study biological systems and diseases, as well as to develop and evaluate medical treatments. The term "in silico" indicates that these processes are carried out via computer simulations and data analysis, as opposed to traditional methods like in vitro (test tube or cell culture) or in vivo (live organism) studies.

The Information Visualization Reference Model is a framework that provides a structured approach to understanding, designing, and evaluating information visualization systems. It helps in conceptualizing how information can be represented visually and guides the development of effective visualizations. The model typically includes key components that outline the various aspects of the visualization process, from data representation to user interaction.

The Irish Centre for High-End Computing (ICHEC) is a national center in Ireland that provides high-performance computing (HPC) resources and services to researchers and institutions across the country. Established to support scientific research and innovation, ICHEC offers access to advanced computational resources, expertise in high-performance computing techniques, and assistance in using these resources effectively for various applications.

Irrigation informatics is an interdisciplinary field that combines principles from irrigation engineering, data science, information technology, and agricultural science to improve the management of irrigation systems. It involves the collection, analysis, and application of data related to water use, soil conditions, crop growth, weather patterns, and irrigation practices. The goal is to optimize the efficiency of irrigation systems, enhance crop yields, conserve water resources, and support sustainable agricultural practices.

The Ken Kennedy Award is presented annually to recognize an individual who has made significant contributions to the field of computing, particularly in the areas related to the use of computing to solve large-scale, complex problems. Named in honor of Ken Kennedy, a prominent computer scientist known for his work in high-performance computing and programming languages, the award aims to highlight the importance of leadership and innovation in the field.

Lateral computing is a concept that refers to a shift in the way that computing resources are organized, allocated, and optimized to enhance performance and efficiency across different paradigms, such as cloud computing, edge computing, and distributed systems. While the term may not be widely standardized, it generally emphasizes the following ideas: 1. **Decentralization:** Moving away from traditional centralized computing models to embrace a more distributed architecture.

I'm sorry, but I don't have access to real-time databases or specific event information, including the list of keynote speakers for events such as the Intelligent Systems for Molecular Biology (ISMB) conference.

Subcellular localization prediction tools are designed to predict where proteins reside within a cell, based on their sequence or structural features. Here’s a list of some well-known protein subcellular localization prediction tools: 1. **SignalP**: Predicts the presence and location of signal peptide cleavage sites in prokaryotic and eukaryotic proteins. 2. **TargetP**: Predicts the subcellular localization of proteins in eukaryotes based on N-terminal targeting signals.