Add to ORKGKey words: knowledge discovery and data mining, machine learning, eukaryotic promoter recognition, transcription factor binding sites SUMMARY Motivation: Numerous principles of constructing classifications are currently known. We propose the definition of “natural ” classification and based on the definition a principally new approach to the classifications of nucleotide sequences. Results: A method for constructing the “natural ” classification, algorithm, and software system DNANatClass have been developed. As the application result we propose the regularities matrices describing SF1 and EGR1 transcription factor binding sites
<div><p>Understanding the molecular machinery involved in transcriptional regulation is central to i...
Despite the fact that each cell in an organism has the same genetic information, it is possible that...
Transcription factor-DNA interactions, central to cellular regulation and control, are commonly desc...
Motivation: Analysis of gene regulatory sequences is of great interest for understanding molecular m...
To try to increase the accuracy of transcription factor binding site prediction we propose a new app...
In this paper we apply machine learning to the task of predicting transcription factor binding sites...
Regulation of gene expression is pivotal to cell behavior. It is achieved predominantly by transcrip...
Understanding the molecular machinery involved in transcriptional regulation is central to improving...
In computational methods, position weight matrices (PWMs) are commonly applied for transcription fac...
Regulatory sequence detection is a fundamental challenge in computational biology. One key process i...
A transcription factor (TF) is a protein or protein complex. It regulates the expression of its targ...
Key words: transcription factor binding sites recognition, lipid metabolism, endocrine system, gene...
Abstract Background Transcription factors function by binding different classes of regulatory elemen...
The discovery of gene regulatory elements requires the synergism between computational and experimen...
The identification of cis-regulatory binding sites in DNA is a difficult problem in computational bi...
<div><p>Understanding the molecular machinery involved in transcriptional regulation is central to i...
Despite the fact that each cell in an organism has the same genetic information, it is possible that...
Transcription factor-DNA interactions, central to cellular regulation and control, are commonly desc...
Motivation: Analysis of gene regulatory sequences is of great interest for understanding molecular m...
To try to increase the accuracy of transcription factor binding site prediction we propose a new app...
In this paper we apply machine learning to the task of predicting transcription factor binding sites...
Regulation of gene expression is pivotal to cell behavior. It is achieved predominantly by transcrip...
Understanding the molecular machinery involved in transcriptional regulation is central to improving...
In computational methods, position weight matrices (PWMs) are commonly applied for transcription fac...
Regulatory sequence detection is a fundamental challenge in computational biology. One key process i...
A transcription factor (TF) is a protein or protein complex. It regulates the expression of its targ...
Key words: transcription factor binding sites recognition, lipid metabolism, endocrine system, gene...
Abstract Background Transcription factors function by binding different classes of regulatory elemen...
The discovery of gene regulatory elements requires the synergism between computational and experimen...
The identification of cis-regulatory binding sites in DNA is a difficult problem in computational bi...
<div><p>Understanding the molecular machinery involved in transcriptional regulation is central to i...
Despite the fact that each cell in an organism has the same genetic information, it is possible that...
Transcription factor-DNA interactions, central to cellular regulation and control, are commonly desc...