scholarly journals eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

2021 ◽  
Author(s):  
Carlos P Cantalapiedra ◽  
Ana Hernandez-Plaza ◽  
Ivica Letunic ◽  
Peer Bork ◽  
Jaime Huerta-Cepas
Keyword(s):  
Functional Annotation ◽  
De Novo ◽  
Gene Prediction ◽  
Protein Domain ◽  
Data Sets ◽  
Online Service ◽  
De Novo Gene ◽  
Orthology Prediction ◽  
Domain Prediction ◽  
Domain Discovery

Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows: (i) de novo gene prediction from raw contigs, (ii) built-in pairwise orthology prediction, (iii) fast protein domain discovery, and (iv) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

scholarly journals eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

2021 ◽  
Author(s):  
Carlos P Cantalapiedra ◽  
Ana Hernández-Plaza ◽  
Ivica Letunic ◽  
Peer Bork ◽  
Jaime Huerta-Cepas
Keyword(s):  
Functional Annotation ◽  
De Novo ◽  
Gene Prediction ◽  
Protein Domain ◽  
Data Sets ◽  
Online Service ◽  
De Novo Gene ◽  
Orthology Prediction ◽  
Domain Prediction ◽  
Domain Discovery

Abstract Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: (i) de novo gene prediction from raw contigs, (ii) built-in pairwise orthology prediction, (iii) fast protein domain discovery, and (iv) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

scholarly journals CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction

2007 ◽  
Vol 8 (12) ◽  
pp. R269 ◽  
Author(s):  
Samuel S Gross ◽  
Chuong B Do ◽  
Marina Sirota ◽  
Serafim Batzoglou
Keyword(s):  
De Novo ◽  
Gene Prediction ◽  
De Novo Gene

scholarly journals Using ESTs to improve the accuracy of de novo gene prediction

2006 ◽  
Vol 7 (1) ◽  
Author(s):  
Chaochun Wei ◽  
Michael R Brent
Keyword(s):  
De Novo ◽  
Gene Prediction ◽  
De Novo Gene

scholarly journals De novo assembly of trachidermus fasciatus genome by nanopore sequencing

2020 ◽  
Author(s):  
Gangcai Xie ◽  
Xu Zhang ◽  
Feng Lv ◽  
Mengmeng Sang ◽  
Hairong Hu ◽  
...  
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Gene Prediction ◽  
Protein Coding ◽  
De Novo Gene ◽  
Long Reads ◽  
Resource Protection ◽  
Trachidermus Fasciatus ◽  
Roughskin Sculpin ◽  
High Quality Genome

AbstractTrachidermus fasciatus is a roughskin sculpin fish widely located at the coastal areas of East Asia. Due to the environmental destruction and overfishing, the populations of this species have been under threat. It is important to have a reference genome to study the population genetics, domestic farming, and genetic resource protection. However, currently, there is no reference genome for Trachidermus fasciatus, which has greatly hurdled the studies on this species. In this study, we proposed to integrate nanopore long reads sequencing, Illumina short reads sequencing and Hi-C methods to thoroughly de novo assemble the genome of Trachidermus fasciatus. Our results provided a chromosome-level high quality genome assembly with a total length of about 543 Mb, and with N50 of 23 Mb. Based on de novo gene prediction and RNA sequencing information, a total of 38728 genes were found, including 23191 protein coding genes, 2149 small RNAs, 5572 rRNAs, and 7816 tRNAs. Besides, about 23% of the genome area is covered by the repetitive elements. Furthermore, The BUSCO evaluation of the completeness of the assembled genome is more than 96%, and the single base accuracy is 99.997%. Our study provided the first whole genome reference for the species of Trachidermus fasciatus, which might greatly facilitate the future studies on this species.

scholarly journals De Novo Sporophyte Transcriptome Assembly and Functional Annotation in the Endangered Fern Species Vandenboschia speciosa (Willd.) G. Kunkel

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1017
Author(s):  
Mohammed Bakkali ◽  
Rubén Martín-Blázquez ◽  
Mercedes Ruiz-Estévez ◽  
Manuel A. Garrido-Ramos
Keyword(s):  
Functional Annotation ◽  
Vascular Plants ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Systematic Position ◽  
Important Data ◽  
Ecological Requirements ◽  
Physiological Adaptations ◽  
Fern Species ◽  
Go Terms

We sequenced the sporophyte transcriptome of Killarney fern (Vandenboschia speciosa (Willd.) G. Kunkel). In addition to being a rare endangered Macaronesian-European endemism, this species has a huge genome (10.52 Gb) as well as particular biological features and extreme ecological requirements. These characteristics, together with the systematic position of ferns among vascular plants, make it of high interest for evolutionary, conservation and functional genomics studies. The transcriptome was constructed de novo and contained 36,430 transcripts, of which 17,706 had valid BLAST hits. A total of 19,539 transcripts showed at least one of the 7362 GO terms assigned to the transcriptome, whereas 6547 transcripts showed at least one of the 1359 KEGG assigned terms. A prospective analysis of functional annotation results provided relevant insights on genes involved in important functions such as growth and development as well as physiological adaptations. In this context, a catalogue of genes involved in the genetic control of plant development, during the vegetative to reproductive transition, in stress response as well as genes coding for transcription factors is given. Altogether, this study provides a first step towards understanding the gene expression of a significant fern species and the in silico functional and comparative analyses reported here provide important data and insights for further comparative evolutionary studies in ferns and land plants in general.

Online Third Places: Supporting Well-Being Through Identifying and Managing Unintended Consequences

2021 ◽  
pp. 109467052110188
Author(s):  
Joy Parkinson ◽  
Lisa Schuster ◽  
Rory Mulcahy
Keyword(s):  
Well Being ◽  
Unintended Consequences ◽  
Abductive Reasoning ◽  
Service Research ◽  
Data Sets ◽  
Management Service ◽  
Consumer Empowerment ◽  
Online Service ◽  
Third Places ◽  
Third Place

Unintended consequences of service are important yet infrequently examined in transformative service research. This research examines an online service community that transformed into an online third place, with consumers socializing and forming lasting relationships. Using practice-informed theory-building and an abductive reasoning approach, findings are presented from both manual and automated coding of three qualitative data sets that form the basis of a case study examining an online weight management service forum. Extending beyond current conceptualizations of the third place, this study is the first to propose a framework delineating online third place characteristics and their impact on consumers’ eudaimonic (the capacity for self-realization) and hedonic (attainment of pleasure and avoidance of pain) well-being. Findings show that in the absence of a physical or virtual servicescape, social factors including social density, equity, and personalization are key to constructing an online third place that supports well-being through building social connections and enjoyment. The new framework provides guidance for service managers to transform their online service communities into online third places to support consumer well-being and to identify and manage potential unintended consequences, for example, by ensuring segmentation of the community based on consumer groups’ shared interests and consumer empowerment through participation.

scholarly journals Fine-tuning of a generative neural network for designing multi-target compounds

2021 ◽  
Author(s):  
Thomas Blaschke ◽  
Jürgen Bajorath
Keyword(s):  
Neural Network ◽  
Small Molecules ◽  
De Novo ◽  
Pharmaceutical Research ◽  
Generative Models ◽  
Fine Tuning ◽  
Data Sets ◽  
Single Target ◽  
Fine Tune ◽  
Target Activity

AbstractExploring the origin of multi-target activity of small molecules and designing new multi-target compounds are highly topical issues in pharmaceutical research. We have investigated the ability of a generative neural network to create multi-target compounds. Data sets of experimentally confirmed multi-target, single-target, and consistently inactive compounds were extracted from public screening data considering positive and negative assay results. These data sets were used to fine-tune the REINVENT generative model via transfer learning to systematically recognize multi-target compounds, distinguish them from single-target or inactive compounds, and construct new multi-target compounds. During fine-tuning, the model showed a clear tendency to increasingly generate multi-target compounds and structural analogs. Our findings indicate that generative models can be adopted for de novo multi-target compound design.

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