1. Classification of seed members of five riboswitch families as short sequences based on the features extracted by Block Location-Based Feature Extraction (BLBFE) method

Faegheh Golabi , Elnaz Mehdizadeh Aghdam , Mousa Shamsi* , Mohammad Hossein Sedaaghi , Abolfazl Barzegar , Mohammad Saeid Hejazi*

BioImpacts. 2021;11(2): 101-109. doi: 10.34172/bi.2021.17

PMCID: PMC8022236 PMID: 33842280 Scopus ID: 85106631206

Article

PDF

Full Text

XML

Cited By:

Block Location-Based Feature Extraction strategy (BLBFE) method was recently introduced as an alignment-free algorithm to classify riboswitches. Employing BLBFE method accompanied by KNN or decision tree classifiers results in better performance in the classification of riboswitches.

Original Article

2. Hybrid deep learning models for text-based identification of gene-disease associations

Noor Fadhil Jumaa , Jafar Razmara* , Sepideh Parvizpour, Jaber Karimpour

Bioimpacts. 2025;15: 31226 | Published on: 2025 Jun 28. doi: 10.34172/bi.31226

Article

PDF

Suppl 1

XML

Cited By:

Submit Your Paper Instructions for Authors Aims and Scope Editorial Board Editorial Policies Publication Ethics Policies Editorial Board Policy Abstracting and Indexing Archive

As a peer-reviewed international open-access journal, BioImpacts publishes articles on basic and translational aspects of pharmaceutical and biomedical sciences.
Acceptance rate (2024): 20%
Publication fee: Free of charge

Indexing/Abstracting Info
PubMed; PubMed Central; Scopus; Science Citation Index Expanded; Google Scholar; SJR; Essential Science Indicators; Embase; EBSCOhost; CAS: DOAJ: SHERPA/RoMEO
Member of
Follower of ICMJE
Permission: Creative Commons