Alessandra Tucci | Personalized Medicine | Women Researcher Award

Posted on by sciencefather

Alessandra Tucci | Personalized Medicine | Women Researcher Award

Dr. Alessandra Tucci, ASST Spedali Civili di Brescia, Italy

Dr. Alessandra Tucci is an esteemed Italian hematologist and Director of the Hematology Unit at ASST Spedali Civili di Brescia. With over three decades of expertise, she specializes in lymphomas, particularly in elderly patients. She holds dual specializations in Allergology & Immunology (University of Florence) and Hematology (University of Milan). A key figure in national and international research, she has led multiple clinical trials and serves on prestigious scientific boards, including the Italian Lymphoma Foundation (FIL) and European Hematology Association (EHA). An accomplished author and peer reviewer, Dr. Tucci continues to advance hematological research.

Publication Profile

Scopus

Education

Dr. Alessandra Tucci 🎓 earned her Doctor of Medicine degree from the University of Brescia in 1987, specializing in Allergology, Immunology, and Hematology. 🩸 Her dual specialization underscores her deep expertise in blood disorders and immune-related conditions. 🏥 Passionate about advancing medical science, she further pursued a Master’s in Management applied to hematology, showcasing her leadership in clinical and research settings. 📚 With a strong foundation in both patient care and scientific innovation, Dr. Tucci continues to make significant contributions to the field, bridging the gap between medical research and practical healthcare solutions. 🔬✨

Experience

Dr. Alessandra Tucci 🔬 is a Principal Investigator in numerous national and international studies, focusing on hematology, particularly lymphomas and hematologic malignancies in elderly patients. 🩸 Her research impact is evident through an impressive H-index of 44 (Scopus) and 48 (Google Scholar), with over 9,792 citations. 📊 She has contributed as a Guest Editor for Special Issues in high-impact journals like Cancers and serves as a reviewer for prestigious publications such as Lancet Haematology and Blood Advances. 📖 Her dedication to advancing hematologic research continues to shape the field and improve patient outcomes worldwide.

Awards

Dr. Alessandra Tucci 🏆 has played a pivotal role in clinical trials (phases I-III), driving innovative treatments in hematology and significantly improving patient care. 🩸 Her contributions extend beyond research, as she actively shapes the scientific community through editorial work, peer reviews, and participation in prestigious scientific boards. 📖🔬 Recognized for her expertise and leadership, she is a respected thought leader whose work influences both clinical practice and future therapeutic advancements. 🌍✨ Through her dedication, Dr. Tucci continues to leave a lasting impact on the field of hematology, inspiring researchers and improving patient outcomes worldwide. 💡👩‍⚕️

Research Focus

Dr. Alessandra Tucci is a distinguished researcher specializing in hematology 🩸, with a focus on lymphomas 🦠, leukemias 🧬, and stem cell transplantation 🏥. Her work extensively explores invasive pulmonary aspergillosis in leukemia, mantle cell lymphoma prognosis, and the impact of radiotherapy on hematologic malignancies. She contributes to clinical trials, geriatric oncology assessments, and advanced imaging techniques like FDG PET/CT 📡 to improve diagnostic precision and treatment outcomes. Dr. Tucci’s research plays a critical role in optimizing chemoimmunotherapy 💉 and personalized medicine for hematologic disorders.

Publication Top Notes

Different Epidemiology of Invasive Pulmonary Aspergillosis in Acute Lymphoblastic Leukemia in Comparison With Acute Myeloid Leukemia: Results of a Prospective Multicentric Observational Study of the Rete Ematologica Lombarda

Impact of the Number of Administered Systemic Treatment Lines on Local Response to Radiation Therapy for Multiple Myeloma

A phase 2 study of autologous stem cell transplantation as salvage therapy for older patients with aggressive B-cell lymphoma prospectively evaluated by comprehensive geriatric assessment: the FIL_RECANZ study

Prognostic Role of Pretreatment Tumor Burden and Dissemination Features From 2-[18F]FDG PET/CT in Advanced Mantle Cell Lymphoma

Early progression beyond first-line chemoimmunotherapy in follicular lymphoma: Insights from a Fondazione Italiana Linfoma (FIL) study

Omission of Radiotherapy in Primary Mediastinal B-Cell Lymphoma: IELSG37 Trial Results

Correction: Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19 (Genome Medicine, (2023), 15, 1, (22), 10.1186/s13073-023-01173-8)

Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection

Local radiotherapy and measurable residual disease-driven immunotherapy in patients with early-stage follicular lymphoma (FIL MIRO): final results of a prospective, multicentre, phase 2 trial
2-[18]F FDG PET/CT dissemination features in adult burkitt lymphoma Are predictive of outcome

Qingfeng Chen | Bioinformatics in Pharmaceuticals | Best Researcher Award

Posted on by sciencefather

Qingfeng Chen | Bioinformatics in Pharmaceuticals | Best Researcher Award

Prof Qingfeng Chen, Guangxi University, China

Prof. Qingfeng Chen is a distinguished leader in bioinformatics, data mining, and artificial intelligence. With a Ph.D. in Computer Science from the University of Technology Sydney, he has made significant contributions to drug-target interaction prediction, RNA structure identification, and protein kinase regulation. An active academic leader, he serves as the Chairman of the Guangxi Bioinformatics Association and has held editorial roles in top journals. His extensive publication record and leadership in international conferences reflect his influence. Prof. Chen’s mentorship and dedication to advancing interdisciplinary research make him a trailblazer in his field. 📚💻🔬🌍

Publication Profile

scopus

Educational Backgrounds

Professor Qingfeng Chen holds a Doctor of Philosophy in Computer Science and Technology from the University of Technology Sydney (2004) 🎓. He earned a Master of Mathematics from Guangxi Normal University in 1998, following his Bachelor’s degree in Mathematics from the same institution in 1995 📚. His academic journey reflects a strong foundation in both mathematics and computer science, positioning him as an expert in these fields. With a distinguished academic background, Prof. Chen continues to contribute significantly to the advancement of technology and mathematical research 🔍.

Editorial Role

Prof. Qingfeng Chen is a highly regarded academic, serving as an Associated Editor for Complexity & Intelligent Systems and the Journal of Bioinformatics. He has also contributed as a Guest Editor for notable journals such as Current Protein & Peptide Science, Engineering Letters, and IAENG (International Association of Engineers). Additionally, Prof. Chen serves as a Journal Reviewer for esteemed publications, including Data Mining and Knowledge Discovery, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Information Technology in Biomedicine, Briefing in Bioinformatics, Information Science, Knowledge and Information Systems, and IEEE Transactions on Evolutionary Computation 📚💻🔬.

Current Position

Prof. Qingfeng Chen has held several prestigious positions throughout his career. Since July 2009, he has been a Professor of Bioinformatics, Data Mining, and Artificial Intelligence at the Department of Computer and Electronic Information, Guangxi University. He has also served as an Honorary Research Fellow at La Trobe University in Australia since May 2016. In addition, he is the Chairman of the Guangxi Bioinformatics Association (since August 2022) and the Executive Deputy Director of the Biomedical Informatics Committee of the Guangxi Artificial Intelligence Society (since August 2020). Previously, he was an Honorary Visiting Professor at the University of Technology Sydney and a Research Fellow at City University of Hong Kong 🔬🎓🌍.

Conference Leadership

Prof. Qingfeng Chen has made significant contributions to the academic community, not only through his impactful research and publications but also by showcasing his leadership in organizing key conferences. He has chaired prominent events such as the 12th International Conference on Bioinformatics and Biomedical Science (ICBBS 2023), where his expertise guided discussions on bioinformatics and biomedical advancements. Additionally, he has co-chaired several other international conferences, highlighting his dedication to advancing bioinformatics and artificial intelligence. Through these efforts, Prof. Chen continues to shape and influence the future of these rapidly evolving fields 📅💡🌍.

Extensive Research

Prof. Qingfeng Chen has published a vast array of influential papers and monographs, establishing himself as a leader in bioinformatics. His groundbreaking work in drug-target interaction prediction, RNA structure identification, and protein kinase regulation is highly respected. Notable books such as Intelligent Strategies for Pathway Mining and Secure Transaction Protocol Analysis highlight his expertise in computational biology. Prof. Chen’s journal papers, covering topics like circRNA-disease association prediction and the evolution of SARS-CoV-2, are widely cited and published in prestigious journals like IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Computational Biology and Bioinformatics 📖🔬💡.

Research Focus

Professor Qingfeng Chen’s research primarily focuses on advanced computational biology, particularly in the integration and analysis of multi-omics data for precision medicine. His work involves developing machine learning frameworks, such as interpretable multitask learning models and graph convolutional networks, for predicting cancer outcomes, understanding immune responses, and improving drug-target interaction predictions. His research also explores the application of deep learning techniques to predict responses to therapies like immune checkpoint inhibitors. With a keen interest in cancer biology, his studies aim to enhance biomarker discovery and optimize therapeutic strategies. 🔬💡

Publication Top Notes

scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis

Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma

A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks

Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma

Bi-SGTAR: A simple yet efficient model for circRNA-disease association prediction based on known association pair only

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery

IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability

Entity Alignment Based on Dynamic Graph Attention and Label Propagation

NGCN: Drug-target interaction prediction by integrating information and feature learning from heterogeneous network