On DNA numerical representations for genomic similarity computation
نویسندگان
چکیده
منابع مشابه
On DNA numerical representations for genomic similarity computation
Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when usi...
متن کاملComputation of Similarity - Similarity Search as Computation
We present a number of applications in Natural Language Processing where the main computation consists of a similarity search for an input pattern in a large database. Afterwards we describe some efficient methods and algorithms for solving this computational challenge. We discuss the view of the similarity search as a special kind of computation, which is remarkably common in applications of C...
متن کاملSentence Similarity on Structural Representations
Most previous approaches used various kinds of plain similarity features to represent the similarity of a sentence pair, and one of its limitations is its weak representation ability. This paper introduces the relational structures representation (shallow syntactic tree, dependency tree) to compute sentence similarity. Experimental results manifest that our approach achieves higher performance ...
متن کاملLearning Representations for Evolutionary Computation
Evolutionary systems have been used in a variety of applications, from turbine design to scheduling problems. The basic algorithms are similar in all these applications, but the representation is always problem specific. Unfortunately, the search time for evolutionary systems very much depends on efficient codings, using problem specific domain knowledge to reduce the size of the search space. ...
متن کاملSimilarity and dissimilarity in correlations of genomic DNA
We analyze auto-correlations of human chromosomes 1–22 and rice chromosomes 1–12 for seven binary mapping rules and find that the correlation patterns are different for different rules but almost identical for all of the chromosomes, despite their varying lengths and gc contents. We propose a simple stochastic process for modeling these correlations, and we find that the proposed process can re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2017
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0173288