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In this paper we experiment with using neural network structures to predict a protein's secondary structure ({\alpha} helix positions) from only its primary structure (amino acid sequence). We implement a fully connected neural network…

Machine Learning · Computer Science 2022-08-25 Sidharth Malhotra , Robin Walters

We view the folding of RNA-sequences as a map that assigns a pattern of base pairings to each sequence, known as secondary structure. These preimages can be constructed as random graphs (i.e. the neutral networks associated to the structure…

adap-org · Physics 2008-02-03 Christian V. Forst , Christian Reidys , Jacqueline Weber

In this paper we consider the problem of RNA folding with pseudoknots. We use a graphical representation in which the secondary structures are described by planar diagrams. Pseudoknots are identified as non-planar diagrams. We analyze the…

Biomolecules · Quantitative Biology 2007-05-23 G. Vernizzi , H. Orland , A. Zee

We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of ${\cal O}(N^6)$ in time and ${\cal O}(N^4)$ in storage. The description of the…

Biological Physics · Physics 2009-09-25 Elena Rivas , Sean R. Eddy

Structured RNA plays many functionally relevant roles in molecular life. Structural information, while required to understand the functional cycles in detail, is challenging to gather. Computational methods promise to complement…

Molecular Networks · Quantitative Biology 2019-04-16 Fabrizio Pucci , Alexander Schug

We introduce a novel fully convolutional neural network (FCN) architecture for predicting the secondary structure of ribonucleic acid (RNA) molecules. Interpreting RNA structures as weighted graphs, we employ deep learning to estimate the…

Biomolecules · Quantitative Biology 2024-06-07 Marc Harary , Chengxin Zhang

Predicting protein secondary structure is a fundamental problem in protein structure prediction. Here we present a new supervised generative stochastic network (GSN) based method to predict local secondary structure with deep hierarchical…

Quantitative Methods · Quantitative Biology 2014-03-07 Jian Zhou , Olga G. Troyanskaya

A hierarchical model for the growth of planar arch structures for RNA secondary structures is presented, and shown to be equivalent to a tree-growth model. Both models can be solved analytically, giving access to scaling functions for large…

Biomolecules · Quantitative Biology 2008-04-11 Francois David , Christian Hagendorf , Kay Joerg Wiese

The Gene or DNA sequence in every cell does not control genetic properties on its own; Rather, this is done through translation of DNA into protein and subsequent formation of a certain 3D structure. The biological function of a protein is…

Computational Engineering, Finance, and Science · Computer Science 2019-05-30 Leila Khalatbari , Mohammad Reza Kangavari , Saeid Hosseini , Hongzhi Yin , Ngai-Man Cheung

The primary structure of a ribonucleic acid (RNA) molecule can be represented as a sequence of nucleotides (bases) over the alphabet {A, C, G, U}. The secondary or tertiary structure of an RNA is a set of base pairs which form bonds between…

Data Structures and Algorithms · Computer Science 2015-01-05 Shihyen Chen , Zhuozhi Wang , Kaizhong Zhang

The alignment of biological sequences such as DNA, RNA, and proteins, is one of the basic tools that allow to detect evolutionary patterns, as well as functional/structural characterizations between homologous sequences in different…

Quantitative Methods · Quantitative Biology 2023-05-01 Louise Budzynski , Andrea Pagnani

We consider Convolutional Neural Networks (CNNs) with 2D structured features that are symmetric in the spatial dimensions. Such networks arise in modeling pairwise relationships for a sequential recommendation problem, as well as secondary…

Machine Learning · Statistics 2022-03-07 Kehelwala Dewage Gayan Maduranga , Vasily Zadorozhnyy , Qiang Ye

Sequences of nucleotides (for DNA and RNA) or amino acids (for proteins) are central objects in biology. Among the most important computational problems is that of sequence alignment, i.e. arranging sequences from different organisms in…

Quantitative Methods · Quantitative Biology 2020-12-08 Anna Paola Muntoni , Andrea Pagnani , Martin Weigt , Francesco Zamponi

Prediction of one-dimensional protein structures such as secondary structures and contact numbers is useful for the three-dimensional structure prediction and important for the understanding of sequence-structure relationship. Here we…

Biomolecules · Quantitative Biology 2007-05-23 Akira R. Kinjo , Ken Nishikawa

Predicting protein structure from amino acid sequence is one of the most important unsolved problems of molecular biology and biophysics.Not only would a successful prediction algorithm be a tremendous advance in the understanding of the…

Computational Engineering, Finance, and Science · Computer Science 2010-06-15 K. K Senapati , G. Sahoo , D. Bhaumik

RNA, whose functionality is largely determined by its structure, plays an important role in many biological activities. The prediction of pairwise structural proximity between each nucleotide of an RNA sequence can characterize the…

Quantitative Methods · Quantitative Biology 2024-01-22 Yiren Jian , Chongyang Gao , Chen Zeng , Yunjie Zhao , Soroush Vosoughi

Metrics for indirectly predicting the folding rates of RNA sequences are of interest. In this letter, we introduce a simple metric of RNA structural complexity, which accounts for differences in the energetic contributions of RNA base…

Biomolecules · Quantitative Biology 2009-08-17 Asamoah Nkwanta , Wilfred Ndifon

Motivation: Non-coding RNAs (ncRNAs) express their functions by adopting molecular structures. Specifically, RNA secondary structures serve as a relatively stable intermediate step before tertiary structures, offering a reliable signature…

Data Structures and Algorithms · Computer Science 2024-02-07 Bertrand Marchand , Yoann Anselmetti , Manuel Lafond , Aïda Ouangraoua

Non-coding RNAs are ubiquitous, but the discovery of new RNA gene sequences far outpaces research on their structure and functional interactions. We mine the evolutionary sequence record to derive precise information about function and…

Biomolecules · Quantitative Biology 2016-04-22 Caleb Weinreb , Adam J. Riesselman , John B. Ingraham , Torsten Gross , Chris Sander , Debora S. Marks

Proteins are the basic building blocks of life. They usually perform functions by folding to a particular structure. Understanding the folding process could help the researchers to understand the functions of proteins and could also help to…

Computational Engineering, Finance, and Science · Computer Science 2015-10-21 Jianzhu Ma