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International Journal of Cheminformatics Cover

International Journal of Cheminformatics

| Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

International Journal of Cheminformatics is a peer-reviewed hybrid open-access journal launched in 2023 that aims to serve as a platform for the propagation of innovative ideas and research in all areas of Cheminformatics. All manuscripts undergo a rigorous peer-review process. It is designed to create interest among researchers in this field, which deals with the use of computer and information techniques applied to a wide range of problems in the field of chemistry. The main functions of this journal are in the areas of topology, chemical graph theory, information retrieval, and data mining in the chemical field. Cheminformatics can also be used in chemical and allied industries in several other forms. The journal aims to publish original, high-quality papers that are peer-reviewed by our expert editorial team to ensure the publication of only good-quality papers.

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Journal Information

Title: International Journal of Cheminformatics
Abbreviation: ijci
Issues Per Year: 2 Issues
Publisher: STM Journals
DOI: 10.37591/IJCI
Starting Year: 2023
Subject: Cheminformatics
Publication Format: Hybrid Open Access
Language: English
Copyright Policy: CC BY-NC-ND
Type: Peer-reviewed Journal (Refereed Journal)

Address:

STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd. A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin - 201301

Editorial Board

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ijci maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Renjith Thomas, Dean, Global Partnership & Innovation

St Berchmans College, Kerala, India,

Email :

Latest Articles

Ahead of Print

Iron Oxide/Chitosan Nanocomposite: Properties and Design for AI Enhanced Immunotherapy and Regenerative Medicine

Biopolymers are valuable complex materials. They attract attentions of many scientists, engineers, and medical professionals’ due to their distinguished properties for various applications.

Biopolymers, Fe3O4/Chitosan nanocomposite, green synthesis, drug delivery, immunotherapy, regenerative medicine

A Literature Survey on Biological Activities of Thiazolidine Derivatives

Hetercyclic compounds play a vital role in both chemical and life sciences. Among them ,thiazolidinone represent a significant class, characterized by a five- membered saturated ring containing both sulfur and nitrogen atoms.

Antimicrobial drug, tuberculosis, thiazolidine, biological activities, hetercyclic compounds

Automated Crop Disease Detection Using Convolutional Neural Networks

Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs.

Crop disease detection, convolutional neural networks, image processing, deep learning, agricultural technology, automated diagnostics, plant pathology, sustainable agriculture, dataset preprocessing, real-time deployment

Synthesis, Molecular Docking and Biological Evaluation of Novel Chlorobenzenesulfonamide Analogues of Ibuprofen as Anti-Bacterial, Anti-Diabetic and Anti-Alzheimer Agents

In this work, we have synthesized novel chlorobenzensulfonamide tertiary amide based analogues of Ibuprofen (Ibu) and investigated them for their anti-bacterial, anti-diabetic and anti-Alzheimer activities.

Synthesis, anti-cholinesterase, anti-bacterial, anti-diabetic, α-amylase, α-glucosidase

QSAR Modeling Techniques: A Comprehensive Review of Tools and Best Practices

Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry.

Artificial Intelligence, chemical safety, machine learning, QSAR modeling, toxicity prediction

Big Data in Chemistry: Problems and Answers

The rapid growth of experimental and computational chemistry data, researchers now have access to vast datasets, presenting both significant opportunities and challenges.

Big data in chemistry, cheminformatics, data integration, interdisciplinary collaboration, machine learning in chemistry