scholarly journals TREND: a platform for exploring protein function in prokaryotes based on phylogenetic, domain architecture and gene neighborhood analyses

2020 ◽  
Vol 48 (W1) ◽  
pp. W72-W76 ◽  
Author(s):  
Vadim M Gumerov ◽  
Igor B Zhulin
Keyword(s):  
Protein Function ◽  
Computational Study ◽  
Function Analysis ◽  
Domain Architecture ◽  
Protein Domain ◽  
Homologous Proteins ◽  
Gene Neighborhood ◽  
Protein Domain Architecture ◽  
Key Steps

Abstract Key steps in a computational study of protein function involve analysis of (i) relationships between homologous proteins, (ii) protein domain architecture and (iii) gene neighborhoods the corresponding proteins are encoded in. Each of these steps requires a separate computational task and sets of tools. Currently in order to relate protein features and gene neighborhoods information to phylogeny, researchers need to prepare all the necessary data and combine them by hand, which is time-consuming and error-prone. Here, we present a new platform, TREND (tree-based exploration of neighborhoods and domains), which can perform all the necessary steps in automated fashion and put the derived information into phylogenomic context, thus making evolutionary based protein function analysis more efficient. A rich set of adjustable components allows a user to run the computational steps specific to his task. TREND is freely available at http://trend.zhulinlab.org.

scholarly journals Evolutionary dynamics of protein domain architecture in plants

2012 ◽  
Vol 12 (1) ◽  
pp. 6 ◽  
Author(s):  
Xue-Cheng Zhang ◽  
Zheng Wang ◽  
Xinyan Zhang ◽  
Mi Ha Le ◽  
Jianguo Sun ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Domain Architecture ◽  
Protein Domain ◽  
Protein Domain Architecture

scholarly journals Adaptive Residue-wise Profile Fusion for Low Homologous Protein Secondary Structure Prediction Using External Knowledge

2021 ◽  
Author(s):  
Qin Wang ◽  
Jun Wei ◽  
Boyuan Wang ◽  
Zhen Li ◽  
Sheng Wang ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Protein Function ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Function Analysis ◽  
Protein Secondary Structure ◽  
Protein Secondary Structure Prediction ◽  
Model Learning ◽  
Homologous Proteins ◽  
The Arts

Protein secondary structure prediction (PSSP) is essential for protein function analysis. However, for low homologous proteins, the PSSP suffers from insufficient input features. In this paper, we explicitly import external self-supervised knowledge for low homologous PSSP under the guidance of residue-wise (amino acid wise) profile fusion. In practice, we firstly demonstrate the superiority of profile over Position-Specific Scoring Matrix (PSSM) for low homologous PSSP. Based on this observation, we introduce the novel self-supervised BERT features as the pseudo profile, which implicitly involves the residue distribution in all native discovered sequences as the complementary features. Furthermore, a novel residue-wise attention is specially designed to adaptively fuse different features (i.e., original low-quality profile, BERT based pseudo profile), which not only takes full advantage of each feature but also avoids noise disturbance. Besides, the feature consistency loss is proposed to accelerate the model learning from multiple semantic levels. Extensive experiments confirm that our method outperforms state-of-the-arts (i.e., 4.7% for extremely low homologous cases on BC40 dataset).

Genome-wide identification and expression analysis of the PTP family in Chinese cabbage (Brassica rapa subsp. pekinensis)

Botany ◽  
2019 ◽  
Vol 97 (11) ◽  
pp. 599-614
Author(s):  
Mingfeng Liu ◽  
Jie Ren ◽  
Xueling Ye ◽  
Xin Jiang ◽  
Qingqing Li ◽  
...  
Keyword(s):  
Gene Family ◽  
Brassica Rapa ◽  
Gene Structure ◽  
Chinese Cabbage ◽  
Protein Function ◽  
Tandem Repeats ◽  
Function Analysis ◽  
Expression Patterns ◽  
Protein Tyrosine Phosphatases ◽  
Protein Domain

Protein tyrosine phosphatases (PTPs) are signaling enzymes that play an important role in plant growth and development. Bioinformatics was used to analyze the PTP gene family of Brassica rapa subsp. pekinensis. Forty-six BrPTP family members were identified. These families were divided into eight subfamilies according to the protein domain. The relationship between gene structure and evolution was determined by comparing gene structure with the evolutionary tree. The 46 BrPTP genes were unevenly distributed across the chromosomes, and two pairs were identified to be tandem repeats. The BrPTP domain contained eight important motifs. Motifs of the same subfamily were basically identical, whereas that of each subfamily differed. These common motifs in these subfamilies are essential for PTP protein function. Analysis of BrPTP by quantitative reverse-transcription PCR revealed tissue-specific differences in expression. Most of the BrPTP genes were expressed in the five tissues examined, but not all. Expression patterns under stress showed that most genes were involved in the stress response. Further study of the PTP gene family may reveal more of its functions in Chinese cabbage.

scholarly journals DAVI: a tool for clustering and visualising protein domain architectures

2021 ◽  
Author(s):  
Nathan Jawadi Chadi ◽  
Paul Saighi ◽  
Fabio Rocha Jimenez Vieira ◽  
Juliana Silva Bernardes
Keyword(s):  
Domain Architecture ◽  
Protein Sequences ◽  
Protein Domain ◽  
Computational Approaches ◽  
Prediction Tools ◽  
Protein Functions ◽  
Visualization Tools ◽  
Protein Domain Architecture ◽  
User Friendly

The characterization of protein functions is one of the main challenges in bioinformatics. Proteins are often composed of individual units termed domains, motifs that can evolve independently. The domain architecture of a given protein is the particular order and the content of its numerous domains. Some computational approaches predict the most likely domain architecture for a set of proteins. However, a few numbers of visualization tools exist, and most of them are unavailable. Here we present DAVI, an efficient and user-friendly web server for protein domain architecture clustering and visualization. DAVI accepts the output of most used domain architecture prediction tools and also produces domain architectures for a set of protein sequences. It provides a rich visualization for comparing, analyzing, and visualizing domain architectures.

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