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BioMedInformatics, Volume 3, Issue 4

2023 December - 20 articles

Cover Story: Human immunoglobulin allotypes are allelic antigenic determinants (or ‘markers’) that are determined serologically on human immunoglobulin (IG) or antibody heavy and light chains. These allotypes have been identified on gamma1, gamma2, gamma3 and alpha2 heavy chains (G1m, G2m, G3m and A2m allotypes, respectively) and on kappa light chain (Km allotypes). They represent a major system for understanding the immunogenicity of polymorphic IG chains in relation to amino acid and conformational changes. WHO/IMGT allotype nomenclature and the IMGT unique numbering for constant (C) domain, with the IMGT Collier de Perles graphical representation,  bridge Gm-Am and Km alleles to IGHC and IGKC gene alleles and structures and, by definition, to IG chain immunogenicity, enabling the immunoinformatics of personalized therapeutic antibodies and engineered variants. View this paper
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Articles (20)

  • Article
  • Open Access
6 Citations
3,780 Views
19 Pages

The advancement in technology and the availability of specialized digital signal processing chips have made digital filter design and implementation more feasible in a variety of fields, including biomedical engineering. This paper makes two key cont...

  • Review
  • Open Access
14 Citations
4,589 Views
19 Pages

In pharmaceutical research and development, pursuing novel therapeutics and optimizing existing drugs have been revolutionized by the fusion of cutting-edge technologies and computational methodologies. Over the past few decades, the field of drug de...

  • Review
  • Open Access
70 Citations
20,339 Views
33 Pages

Genomics for Emerging Pathogen Identification and Monitoring: Prospects and Obstacles

  • Vishakha Vashisht,
  • Ashutosh Vashisht,
  • Ashis K. Mondal,
  • Jaspreet Farmaha,
  • Ahmet Alptekin,
  • Harmanpreet Singh,
  • Pankaj Ahluwalia,
  • Anaka Srinivas and
  • Ravindra Kolhe

Emerging infectious diseases (EIDs) pose an increasingly significant global burden, driven by urbanization, population explosion, global travel, changes in human behavior, and inadequate public health systems. The recent SARS-CoV-2 pandemic highlight...

  • Article
  • Open Access
48 Citations
7,763 Views
21 Pages

Enhancing Brain Tumor Classification with Transfer Learning across Multiple Classes: An In-Depth Analysis

  • Syed Ahmmed,
  • Prajoy Podder,
  • M. Rubaiyat Hossain Mondal,
  • S M Atikur Rahman,
  • Somasundar Kannan,
  • Md Junayed Hasan,
  • Ali Rohan and
  • Alexander E. Prosvirin

This study focuses on leveraging data-driven techniques to diagnose brain tumors through magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we introduce and fine-tune two robust frameworks, ResNet 50 and Inception V3,...

  • Case Report
  • Open Access
3 Citations
2,751 Views
12 Pages

Avatar Intervention for Cannabis Use Disorder in a Patient with Schizoaffective Disorder: A Case Report

  • Sabrina Giguère,
  • Laura Dellazizzo,
  • Mélissa Beaudoin,
  • Marie-Andrée Lapierre,
  • Marie Villeneuve,
  • Kingsada Phraxayavong,
  • Stéphane Potvin and
  • Alexandre Dumais

Considering the harmful effects of cannabis on individuals with a severe mental disorder and the limited effectiveness of current interventions, this case report showcases the beneficial results of a 10-session Avatar intervention for cannabis use di...

  • Review
  • Open Access
1 Citations
3,267 Views
11 Pages

Background: Psychotherapy is a component of the therapeutic options accessible in mental health. Along with psychotherapy techniques and indications, there is a body of studies on what are known as psychotherapy’s common factors. However, up to...

  • Article
  • Open Access
18 Citations
5,315 Views
18 Pages

Towards Effective Emotion Detection: A Comprehensive Machine Learning Approach on EEG Signals

  • Ietezaz Ul Hassan,
  • Raja Hashim Ali,
  • Zain ul Abideen,
  • Ali Zeeshan Ijaz and
  • Talha Ali Khan

Emotion detection assumes a pivotal role in the evaluation of adverse psychological attributes, such as stress, anxiety, and depression. This study undertakes an exploration into the prospective capacities of machine learning to prognosticate individ...

  • Article
  • Open Access
5 Citations
2,425 Views
12 Pages

Precision medicine approaches often rely on complex and integrative analyses of multiple biomarkers from “omics” data to generate insights that can help with either diagnostic, prognostic, or therapeutical decisions. Such insights are oft...

  • Article
  • Open Access
1,976 Views
11 Pages

Lung cancer is responsible for the most cancer deaths worldwide, with non-small-cell lung cancer (NSCLC) making up 80% of cases. Some genetic factors leading to NSCLC development include genetic mutations and Programmed Cell Death Ligand 1 (PD-L1) ex...

  • Article
  • Open Access
2 Citations
2,414 Views
20 Pages

Explainable AI-Based Identification of Contributing Factors to the Mood State Change in Children and Adolescents with Pre-Existing Psychiatric Disorders in the Context of COVID-19-Related Lockdowns in Greece

  • Charis Ntakolia,
  • Dimitrios Priftis,
  • Konstantinos Kotsis,
  • Konstantina Magklara,
  • Mariana Charakopoulou-Travlou,
  • Ioanna Rannou,
  • Konstantina Ladopoulou,
  • Iouliani Koullourou,
  • Emmanouil Tsalamanios and
  • Ioanna Giannopoulou
  • + 5 authors

The COVID-19 pandemic and its accompanying restrictions have significantly impacted people’s lives globally. There is an increasing interest in examining the influence of this unprecedented situation on our mental well-being, with less attentio...

  • Article
  • Open Access
2 Citations
3,228 Views
25 Pages

iPSC reprogramming involves dynamic changes in chromatin accessibility necessary for the conversion of somatic cells into induced pluripotent stem cells (iPSCs). IPSCs can be used to generate a wide range of cells to potentially replace damaged cells...

  • Commentary
  • Open Access
3 Citations
3,076 Views
30 Pages

Recent research on selenium-dependent glutathione peroxidase 2 (GPX2) tends to focus on possible roles in tumorigenesis. This is based on the idea that normally generated hydroperoxide species can damage DNA to produce mutations and react with protei...

  • Article
  • Open Access
1 Citations
1,813 Views
23 Pages

Semantic web technologies (SWT) represent data in a format that is easier for machines to understand. Validating the knowledge in data graphs created using SWT is critical to ensure that the axioms accurately represent the so-called “real&rdquo...

  • Article
  • Open Access
29 Citations
7,695 Views
14 Pages

A common consequence of diabetes mellitus called diabetic retinopathy (DR) results in lesions on the retina that impair vision. It can cause blindness if not detected in time. Unfortunately, DR cannot be reversed, and treatment simply keeps eyesight...

  • Article
  • Open Access
7 Citations
3,962 Views
22 Pages

Tacrolimus, characterized by a narrow therapeutic index, significant toxicity, adverse effects, and interindividual variability, necessitates frequent therapeutic drug monitoring and dose adjustments in renal transplant recipients. This study aimed t...

  • Article
  • Open Access
3 Citations
2,079 Views
18 Pages

Identifying the Role of Disulfidptosis in Endometrial Cancer via Machine Learning Methods

  • Fei Fu,
  • Xuesong Lu,
  • Zhushanying Zhang,
  • Zhi Li and
  • Qinlan Xie

Uterine corpus endometrial carcinoma (UCEC) is the second most common gynecological cancer in the world. With the increased occurrence of UCEC and the stagnation of research in the field, there is a pressing need to identify novel UCEC biomarkers. Di...

  • Article
  • Open Access
3 Citations
4,086 Views
23 Pages

We hypothesize that in silico structural biology approaches can discover novel drug binding sites for RNA-dependent-RNA-polymerases (RdRp) of positive sense single-strand RNA (ss(+)RNA) virus species. RdRps have a structurally conserved active site w...

  • Article
  • Open Access
6 Citations
3,149 Views
16 Pages

Recent advances in mathematical modeling and artificial intelligence have challenged the use of traditional regression analysis in biomedical research. This study examined artificial data sets and biomedical data sets from cancer research using binom...

  • Article
  • Open Access
3 Citations
3,370 Views
16 Pages

OutSplice: A Novel Tool for the Identification of Tumor-Specific Alternative Splicing Events

  • Joseph Bendik,
  • Sandhya Kalavacherla,
  • Nicholas Webster,
  • Joseph Califano,
  • Elana J. Fertig,
  • Michael F. Ochs,
  • Hannah Carter and
  • Theresa Guo

Protein variation that occurs during alternative splicing has been shown to play a major role in disease onset and oncogenesis. Due to this, we have developed OutSplice, a user-friendly algorithm to classify splicing outliers in tumor samples compare...

  • Article
  • Open Access
4 Citations
3,743 Views
24 Pages

Weighted Trajectory Analysis and Application to Clinical Outcome Assessment

  • Utkarsh Chauhan,
  • Kaiqiong Zhao,
  • John Walker and
  • John R. Mackey

The Kaplan–Meier (KM) estimator is widely used in medical research to estimate the survival function from lifetime data. KM estimation is a powerful tool to evaluate clinical trials due to simple computational requirements, its use of a logrank...

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BioMedInformatics - ISSN 2673-7426