Vectorization Techniques for Protein Data Analysis: A Position Paper

نویسندگان

  • Srinath Srinivasa
  • Sujit Kumar
چکیده

With the increasing amount of data about the 3D structure of proteins, there is a growing need for computational techniques to analyse these structure data. In our work, we pursue a commonly technique used in On-line Analytical Processing (OLAP) domains – namely the multi-dimensional data model and vectorization of data elements onto multi-dimensional vector spaces. This paper presents preliminary work carried out in this direction and provides a vision for future work.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation

This paper discusses the approach taken by the UWaterloo team to arrive at a solution for the Fine-Grained Sentiment Analysis problem posed by Task 5 of SemEval 2017. The paper describes the document vectorization and sentiment score prediction techniques used, as well as the design and implementation decisions taken while building the system for this task. The system uses text vectorization mo...

متن کامل

Vectorization Techniques for BlueGene/L’s Double FPU

This paper presents vectorization techniques tailored to meet the specifics of the twoway single-instruction multiple-data (SIMD) double-precision floating-point unit, which is a core element of the node ASICs of IBM's 360 Tflop/s supercomputer BlueGene/L. The paper focuses on the general-purpose basic-block vectorization methods provided by the Vienna MAP vectorizer. In addition, the paper int...

متن کامل

Semantical Analysis and Mathematical Programming Application to Parallelization and Vectorization

This paper investigates a new algorithm for solving systems of linear inequalities in the presence of integer parameters. The applications are to various problems in the analysis of scientiic programs. We give methods for computing dependences, for data-ow analysis and for several code generation questions. These techniques all are relevant to the automatic and semi-automatic construction of pr...

متن کامل

Vectorization Using Reversible Data Dependences

Data dependences between statements have long been used for detecting parallelism and converting sequential programs into parallel forms. However, some data dependences can be reversed and the transformed program still produces the same results. In this paper, we revisit vectorization and propose a new vectorization algorithm using reversible data dependences. The new algorithm can generate mor...

متن کامل

High-Level Loop Optimizations for GCC

This paper will present a design for loop optimizations using high-level loop transformations. We will describe a loop optimization infrastructure based on improved induction variable, scalar evolution, and data dependence analysis. We also will describe loop transformation opportunities that utilize the information discovered. These transformations increase data locality and eliminate data dep...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002