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Profil bibliographique

Haseeb Younis

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

18Publications signalées
264Citations signalées
1Affiliations récentes

Les institutions déclarées

Les domaines associés

Plant Stress Responses and TolerancePlant-Microbe Interactions and ImmunityCrop Yield and Soil FertilityPlant Virus Research StudiesAI in cancer detection

Les publications récentes

Accès ouvert 2025 article OpenAlex

Genetic Diversity and Population Structure of Phyllosphere-Associated Xanthomonas euvesicatoria Bacteria in Physalis pubescens Based on BOX-PCR and ERIC-PCR in China

Faisal Siddique, Xiaofeng Xu, Zhe Ni, Naibo Yang et autres

Xanthomonas euvesicatoria has become a serious problem in Physalis pubescens, leading to substantial crop losses. In our previous investigation, we used rapid molecular detection techniques to identify X. euvesicatoria; however, this pathogen's diversity and population structure remain poorly understood, despite their importance …

cn (code pays fourni par la source)

3 citations The Plant Pathology Journal
2024 conference-paper OpenAlex

UNCCER: Unified Network for Cancer Classification and Efficient Representation using Microarray Data

Haseeb Younis, Horiya Imane Brahmi, Jonathan Byrne, Rosane Minghim

In recent years, there has been a significant advance in the use of machine learning (ML) techniques to extract gene expression data from microarray databases, particularly in cancer-related research. There no unified method for classifying cancer microarray data, even after ML adoption. …

ie (code pays fourni par la source)

0 citations
2024 conference-paper OpenAlex

MANet: A Deep Learning Framework for Multi-Cancer Microarray Analysis, Classification, and Visualization

Haseeb Younis, Muhammad Azeem, Isabel Ronan, Rosane Minghim

Machine learning (ML) methods have been used much more frequently in recent years to extract gene expression data from microarray studies, especially in cancer research. Even after the continued interest in applying ML to scientific cancer research, there is still no universal …

ie (code pays fourni par la source)

0 citations
Accès ouvert 2024 article OpenAlex

Effect of abscisic acid on rice defense mechanism against Fusarium oxysporum

Peng Guo, Yang Xiu, Peng Li, Haseeb Younis et autres

Fusarium oxysporum is one of the most destructive pathogens which causes rice seedling blight. ABA is part of a large signaling system that provides an effective system against microbial and environmental manipulations. The role of ABA in plant defense mechanisms is not …

cn (code pays fourni par la source)

0 citations The Journal of Phytology
Accès ouvert 2023 article OpenAlex

Comparative Genomic Analysis and Rapid Molecular Detection of Xanthomonas euvesicatoria Using Unique ATP-Dependent DNA Helicase recQ, hrpB1, and hrpB2 Genes Isolated from Physalis pubescens in China

Faisal Siddique, Xiaofeng Xu, Zhe Ni, Haseeb Younis et autres

Ground cherry (Physalis pubescens) is the most prominent species in the Solanaceae family due to its nutritional content, and prospective health advantages. It is grown all over the world, but notably in northern China. In 2019 firstly bacterial leaf spot (BLS) disease …

cn (code pays fourni par la source)

3 citations The Plant Pathology Journal
2022 article OpenAlex

Exogenous Application of Jasmonic Acid Triggers the Rice Defense Mechanisms against Rhizoctonia solani Kühn

Haseeb Younis, Z. Qingyan, Lei Fu, P. Lili et autres

Abstract Rice sheath blight is caused by the necrotrophic soil-borne fungus Rhizoctonia solani Kühn. It is one of the most destructive rice disease. Jasmonic acid (JA) plays a vital role in plant defense mechanisms. This study aims to increase the understanding of …

cn (code pays fourni par la source)

4 citations Russian Journal of Plant Physiology
Accès ouvert 2022 preprint OpenAlex

Understanding High Dimensional Spaces through Visual Means Employing Multidimensional Projections

Haseeb Younis, Paul Trust, Rosane Minghim

Data visualisation helps understanding data represented by multiple variables, also called features, stored in a large matrix where individuals are stored in lines and variable values in columns. These data structures are frequently called multidimensional spaces.In this paper, we illustrate ways of …

0 citations arXiv (Cornell University)

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