SDRP Journal of Plant Science
  info@siftdesk.org Sign In | Register
  • Home
  • About Us
  • Journals
  • Guidelines
    • Author Guidelines
    • Editor Guidelines
    • Reviewer Guidelines
  • Policies
    • Publication Ethics
    • Peer Review
    • Terms & Conditions
Logo
  • Journal Home
  • Article In Press
  • Current Issue
  • Archive
  • Submit Manuscript
  • Editorial Members
  • Reviewer Members
  • Processing Fee

© 2018 Sift Desk Journals. All Rights Reserved

profile

SDRP Journal of Plant Science

SDRP Journal of Plant Science(SDRP-JPS)

ISSN: 2573-7988

Impact Factor: 0.422

Genome Functional Annotations

Submit Manuscript no this topic Topic Articles: 0

Description

Functional annotation of an entire genome is critical to understand any biological process and its role in biological pathways. Yet, a large part of the human genome, and much more for non-model organisms, remains un-annotated. Simple, sequence-similarity based annotations have been found to be grossly inadequate for this purpose and more sophisticated intelligent systems, such as machine learning have been employed frequently. In its basic formulation, machine-learning techniques found their way into the field of biological functional annotation quite early. Secondary structure prediction using machine learning was done as early as in mid 80’s and many other areas of biological sequence, structure and/or function prediction have seen great advances in terms of the complexity of techniques, feature engineering and other principles of data-driven analytics. Several computational techniques have been developed exclusively for solving functional annotation problems. However, most of the growth has been in terms of the application of emerging and established computational techniques. Machine learning software has often been used as a blackbox tool, while researchers focus on the biological concept of the problem and its solution.

More recently, deep learning methods have made rapid progress and have shown particular success with problems associated with large amounts of biological data. Typically popular amongst them have been convolutional neural networks (CNN), multi-layer feed forward neural networks and long short-term memory (LSTM) networks, along with their variants.

In parallel with machine learning, the biological understanding of molecular function and organization of knowledge on this subject has also undergone rapid advances. Instead of scattered and ambiguous labelling of function, systematic annotations in terms of ontologies, in the form of hierarchical and nested labels have made the task of annotation learning and prediction much more robust.

Much has been achieved on biological and technical aspects of functional annotations but many hurdles remain. Consequently, there are clear opportunities for researchers to fill the gaps.

This Research Topic invites submissions of original research or review papers based on the above framework as outlined but not limited to the description below:
1) From researchers working on intelligent systems and statistical/machine learning techniques for biological function prediction from sequence, structure or gene expression data.
2) Analyzing gene ontologies or specialized functions such as protein-protein or protein-RNA interaction and disease associations.
3) Dealing with biological function as a single unit such as being kinase or protease as well as in a pathway will be considered.
4) Broader biological function prediction or identification of genomic features such as DNA methylation and other genome-wide functional patterns at individual or systems level specifically addressing some aspect of the problem of characterizing the function of genomes annotations. General theoretical methods of artificial intelligence and deep learning without a direct application to these biological problems are out of the scope.

Keywords

Functional annotations; Machine learning; Prediction methods; Protein function; Interaction; Gene Ontology


Journal Archive

Volume: 3 Issue: 1 Volume: 2 Issue: 2 Volume: 2 Issue: 1 Volume: 1 Issue: 1

Journal Recent Articles

By Anastasia Papadaki
N and K interactions in cucumber plants artificially inoculated with P. cubensis
By Anastasia Papadaki
Interactive effects of leaf age and inoculum concentration on downy mildew of cucumber plants and the implication of nutrients.
By Anastasia Papadaki
The impact of potassium on downy mildew of cucumber and its leaf/soil nutritional status.
By xinhong guo
LecRKIII.1 and LecRKIII.2 formed homodimers to play physiological functions in Arabidopsis thaliana
By Anjana
Nitrogenous Fertilizers – Boon or Bane?
By Pavlos Bouchagier
INFERIOR CROP PERFORMANCE IN ORGANIC VINE AND OLIVE SECTOR DUE TO THE POOR IMPLEMENTATION OF QUALITY PROCESSES. THE CASE OF KEFALLINIA.
By Pavlos Bouchagier
Survival of Root-Knot nematodes and their egg-parasitic fungus Pochonia chlamydosporia (Goddard) on weed roots
By Safi-naz S. Zaki
Alleviating Effects of Ascorbic acid and Glutathione for Faba Bean Plants Irrigated with Saline Water.
By Xing-Zheng Wu
Real-time in-situ simultaneous monitoring of dissolved oxygen and materials movements at vicinities of an aquatic plant by fluorescence quenching/deflection with an impro
By Robert M Levin PhD
Effects of Ganoderma Lucidum on Biochemical Dysfunctions of the Rabbit Urinary Bladder using an In-Vitro Model of Ischemia / Reperfusion
By Dr A.S ,Adeyeye
THE GROWTH AND SEED YIELD OF MAIZE VARIETY AS AFFECTED BY TWO LEGUMES INTERCROP
By Edward Missanjo
Seed Biology of Erythrophleum Suaveolens (Guill. and Perr.) Brenan: A Threatened Medicinal Plant
By Bhupendra Singh Adhikari
Sowa-Rigpa: A Healthcare Practice in Trans-Himalayan Region of Ladakh, India
By Muhamed Adem
Application of precise genome editing in plants
By LAKHDARI Wassima
Biological control of Fusarium oxysporum f. sp. radicis lycopersici by using aqueous extracts of medicinal plants of Wadi Righ region

CONTACT US

Sift Desk Journals,
NY, 10022, USA
Call Us: +16469050407
info@siftdesk.org

JOURNALS LINKS

  • Food Science
  • Environmental Studies
  • Computational Chemistry
  • Chemical Engineering
  • Anesthesia & Surgery
  • Cellular & Molecular Physiology
  • Plant Science
  • Aquaculture & Fish Science
  • Nano Technology & Materials Science
  • Allergy & Immunology

QUICK CONTACT

Sift Desk Journals