scholarly journals StartLink and StartLink+: Prediction of Gene Starts in Prokaryotic Genomes

2021 ◽  
Vol 1 ◽  
Author(s):  
Karl Gemayel ◽  
Alexandre Lomsadze ◽  
Mark Borodovsky
Keyword(s):  
Ab Initio ◽  
State Of The Art ◽  
Gene Prediction ◽  
Nucleotide Sequences ◽  
Genomic Databases ◽  
Large Sets ◽  
Multiple Alignments ◽  
A Genome ◽  
Prokaryotic Genomes ◽  
Conservation Patterns

State-of-the-art algorithms of ab initio gene prediction for prokaryotic genomes were shown to be sufficiently accurate. A pair of algorithms would agree on predictions of gene 3′ends. Nonetheless, predictions of gene starts would not match for 15–25% of genes in a genome. This discrepancy is a serious issue that is difficult to be resolved due to the absence of sufficiently large sets of genes with experimentally verified starts. We have introduced StartLink that infers gene starts from conservation patterns revealed by multiple alignments of homologous nucleotide sequences. We also have introduced StartLink+ combining both ab initio and alignment-based methods. The ability of StartLink to predict the start of a given gene is restricted by the availability of homologs in a database. We observed that StartLink made predictions for 85% of genes per genome on average. The StartLink+ accuracy was shown to be 98–99% on the sets of genes with experimentally verified starts. In comparison with database annotations, we observed that the annotated gene starts deviated from the StartLink+ predictions for ∼5% of genes in AT-rich genomes and for 10–15% of genes in GC-rich genomes on average. The use of StartLink+ has a potential to significantly improve gene start annotation in genomic databases.

scholarly journals The Degree of Oxidation of Graphene Oxide

Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 560
Author(s):  
Alexandra Carvalho ◽  
Mariana C. F. Costa ◽  
Valeria S. Marangoni ◽  
Pei Rou Ng ◽  
Thi Le Hang Nguyen ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Ab Initio ◽  
State Of The Art ◽  
High Accuracy ◽  
Precise Determination ◽  
Photoemission Spectroscopy ◽  
Pristine Graphene ◽  
X Ray ◽  
Degree Of Oxidation

We show that the degree of oxidation of graphene oxide (GO) can be obtained by using a combination of state-of-the-art ab initio computational modeling and X-ray photoemission spectroscopy (XPS). We show that the shift of the XPS C1s peak relative to pristine graphene, ΔEC1s, can be described with high accuracy by ΔEC1s=A(cO−cl)2+E0, where c0 is the oxygen concentration, A=52.3 eV, cl=0.122, and E0=1.22 eV. Our results demonstrate a precise determination of the oxygen content of GO samples.

scholarly journals Using Multiple Alignments to Improve Gene Prediction

2006 ◽  
Vol 13 (2) ◽  
pp. 379-393 ◽  
Author(s):  
Samuel S. Gross ◽  
Michael R. Brent
Keyword(s):  
Gene Prediction ◽  
Multiple Alignments

scholarly journals ASPic-GeneID: A Lightweight Pipeline for Gene Prediction and Alternative Isoforms Detection

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Tyler Alioto ◽  
Ernesto Picardi ◽  
Roderic Guigó ◽  
Graziano Pesole
Keyword(s):  
Ab Initio ◽  
Gene Annotation ◽  
Gene Prediction ◽  
Gene Prediction Program ◽  
C Elegans ◽  
Prediction Program ◽  
First Pass ◽  
Main Components ◽  
Genome Projects ◽  
Alternative Isoforms

New genomes are being sequenced at an increasingly rapid rate, far outpacing the rate at which manual gene annotation can be performed. Automated genome annotation is thus necessitated by this growth in genome projects; however, full-fledged annotation systems are usually home-grown and customized to a particular genome. There is thus a renewed need for accurateab initiogene prediction methods. However, it is apparent that fullyab initiomethods fall short of the required level of sensitivity and specificity for a quality annotation. Evidence in the form of expressed sequences gives the single biggest improvement in accuracy when used to inform gene predictions. Here, we present a lightweight pipeline for first-pass gene prediction on newly sequenced genomes. The two main components are ASPic, a program that derives highly accurate, albeit not necessarily complete, EST-based transcript annotations from EST alignments, and GeneID, a standard gene prediction program, which we have modified to take as evidence intron annotations. The introns output by ASPic CDS predictions is given to GeneID to constrain the exon-chaining process and produce predictions consistent with the underlying EST alignments. The pipeline was successfully tested on the entireC. elegansgenome and the 44 ENCODE human pilot regions.

scholarly journals GPRED-GC: a Gene PREDiction model accounting for 5 ′- 3′ GC gradient

2019 ◽  
Vol 20 (S15) ◽  
Author(s):  
Prapaporn Techa-Angkoon ◽  
Kevin L. Childs ◽  
Yanni Sun
Keyword(s):  
Ab Initio ◽  
Gene Annotation ◽  
Gene Prediction ◽  
Source Code ◽  
Gc Content ◽  
Prediction Tools ◽  
Homologous Sequences ◽  
Manual Intervention ◽  
Grass Genomes ◽  
Gc Contents

Abstract Background Gene is a key step in genome annotation. Ab initio gene prediction enables gene annotation of new genomes regardless of availability of homologous sequences. There exist a number of ab initio gene prediction tools and they have been widely used for gene annotation for various species. However, existing tools are not optimized for identifying genes with highly variable GC content. In addition, some genes in grass genomes exhibit a sharp 5 ′- 3′ decreasing GC content gradient, which is not carefully modeled by available gene prediction tools. Thus, there is still room to improve the sensitivity and accuracy for predicting genes with GC gradients. Results In this work, we designed and implemented a new hidden Markov model (HMM)-based ab initio gene prediction tool, which is optimized for finding genes with highly variable GC contents, such as the genes with negative GC gradients in grass genomes. We tested the tool on three datasets from Arabidopsis thaliana and Oryza sativa. The results showed that our tool can identify genes missed by existing tools due to the highly variable GC contents. Conclusions GPRED-GC can effectively predict genes with highly variable GC contents without manual intervention. It provides a useful complementary tool to existing ones such as Augustus for more sensitive gene discovery. The source code is freely available at https://sourceforge.net/projects/gpred-gc/.

scholarly journals Possibility of realizing superionic ice VII in external electric fields of planetary bodies

2020 ◽  
Vol 6 (21) ◽  
pp. eaaz2915 ◽  
Author(s):  
Zdenek Futera ◽  
John S. Tse ◽  
Niall J. English
Keyword(s):  
Molecular Dynamics ◽  
Electric Field ◽  
Ab Initio ◽  
Electric Fields ◽  
State Of The Art ◽  
Ab Initio Molecular Dynamics ◽  
Theoretical Studies ◽  
Potential Candidate ◽  
External Electric Fields ◽  
Ice Phase

In a superionic (SI) ice phase, oxygen atoms remain crystallographically ordered while protons become fully diffusive as a result of intramolecular dissociation. Ice VII’s importance as a potential candidate for a SI ice phase has been conjectured from anomalous proton diffusivity data. Theoretical studies indicate possible SI prevalence in large-planet mantles (e.g., Uranus and Neptune) and exoplanets. Here, we realize sustainable SI behavior in ice VII by means of externally applied electric fields, using state-of-the-art nonequilibrium ab initio molecular dynamics to witness at first hand the protons’ fluid dance through a dipole-ordered ice VII lattice. We point out the possibility of SI ice VII on Venus, in its strong permanent electric field.

scholarly journals A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Nicolas Scalzitti ◽  
Anne Jeannin-Girardon ◽  
Pierre Collet ◽  
Olivier Poch ◽  
Julie D. Thompson
Keyword(s):  
Ab Initio ◽  
Gene Prediction ◽  
Prediction Methods ◽  
Benchmark Study ◽  
Eukaryotic Organisms

scholarly journals Evaluation of five ab initio gene prediction programs for the discovery of maize genes

2005 ◽  
Vol 57 (3) ◽  
pp. 445-460 ◽  
Author(s):  
Hong Yao ◽  
Ling Guo ◽  
Yan Fu ◽  
Lisa A. Borsuk ◽  
Tsui-Jung Wen ◽  
...  
Keyword(s):  
Ab Initio ◽  
Gene Prediction

Ab initio Hartree-Fock treatment of ionic and semi-ionic compounds: state of the art

1992 ◽  
Vol 341 (1661) ◽  
pp. 203-210 ◽  
Keyword(s):  
Ab Initio ◽  
State Of The Art ◽  
Basis Set ◽  
Equilibrium Geometry ◽  
Mulliken Population ◽  
Atomic Orbitals ◽  
Oxygen Ions ◽  
Hartree Fock ◽  
Ionic Compounds ◽  
Mn Oxides

The periodic ab initio Hartree-Fock approach is applied to the Li, Na, K, Be, Mg, Ca and Mn oxides, and to Al 2 O 3 (corundum) and SiO 2 (a-quartz). A local basis set (‘atomic orbitals’) is used. The equilibrium geometry, the formation energy and the bulk modulus are calculated, with reasonable agreement with experiment. The influence of the environment on the oxygen ions is discussed through the Mulliken population and band structure data.

scholarly journals Rovibrational dynamics of the strontium molecule in the AΣu+1, c3Πu, and aΣu+3 manifold from state-of-the-art ab initio calculations

2012 ◽  
Vol 136 (19) ◽  
pp. 194306 ◽  
Author(s):  
Wojciech Skomorowski ◽  
Filip Pawłowski ◽  
Christiane P. Koch ◽  
Robert Moszynski
Keyword(s):  
Ab Initio Calculations ◽  
Ab Initio ◽  
State Of The Art
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