Mingxiong He | Omics Data Analysis | Innovative Research Award

Innovative Research Award

Mingxiong He
Biogas Iinstitute of Ministry of Agriculture and Rural Affairs

Mingxiong He
Affiliation Biogas Iinstitute of Ministry of Agriculture and Rural Affairs
Country China
Scopus ID 18436995800
Documents 133
Citations 4,058
h-index 34
Subject Area Omics Data Analysis
Event Computational Biologists Awards
ORCID 0000-0002-9780-6865

Mingxiong He is a researcher associated with the Biogas Iinstitute of Ministry of Agriculture and Rural Affairs in China. The supplied research profile identifies Omics Data Analysis as the principal subject area and records 133 documents, 4,058 citations, and an h-index of 34 in Scopus. These bibliometric indicators provide a quantitative description of publication activity and citation impact and should be interpreted in relation to field, publication age, collaboration patterns, and database coverage. [1]

Abstract

Mingxiong He is identified in the supplied academic profile as a researcher working in Omics Data Analysis at the Biogas Iinstitute of Ministry of Agriculture and Rural Affairs, China. The profile reports 133 Scopus-indexed documents, 4,058 citations, and an h-index of 34. These indicators describe a substantial body of indexed scholarly output and accumulated citation activity. Omics data analysis integrates computational methods with large-scale biological datasets to characterize molecular patterns and relationships. Such approaches can support genomics, transcriptomics, systems biology, and related research areas. The profile provides a basis for documenting research activity and considering eligibility for recognition through the Computational Biologists Awards.

Keywords

Mingxiong He, Innovative Research Award, Omics Data Analysis, computational biology, bioinformatics, biological data analysis, genomics, molecular data, research impact, Scopus, scholarly publications, Computational Biologists Awards.

Introduction

Omics research generates large and complex datasets that require computational approaches for organization, statistical analysis, interpretation, and biological discovery. Modern multi-omics studies may integrate genomic, transcriptomic, proteomic, metabolomic, and other molecular measurements to investigate biological systems from complementary perspectives. [3] Within this context, computational biology provides methods for transforming high-dimensional biological observations into interpretable research findings.

Research Profile

The supplied Scopus profile records 133 documents, 4,058 citations, and an h-index of 34 for Mingxiong He. The h-index is a bibliometric measure intended to combine publication productivity with citation frequency, while total citation counts reflect accumulated citations across indexed documents. Such metrics are database-dependent and can change over time as new publications and citations are indexed. [1]

Research Contributions

Research contributions within Omics Data Analysis can encompass computational methodology, biological data processing, statistical interpretation, molecular profiling, and integration of heterogeneous datasets. Multi-omics approaches are increasingly used to examine biological processes through complementary molecular layers, allowing researchers to investigate relationships that may not be apparent from a single data type. [3] The supplied profile supports describing Mingxiong He as a researcher working within this computational and data-intensive research environment.

Publications

In omics-oriented research, publications may involve sequencing technologies, molecular profiling, computational pipelines, statistical analysis, or integration of multiple biological datasets. RNA-sequencing analysis illustrates the breadth of computational procedures required to convert sequencing data into biologically interpretable results. [4] The specific publication topics attributable to Mingxiong He should be verified directly through the researcher’s indexed author record and associated publication records.

Research Impact

The supplied profile reports 4,058 citations and an h-index of 34. These measures indicate accumulated citation activity within the indexed research record, but bibliometric indicators should be interpreted alongside disciplinary norms, career duration, collaboration patterns, publication types, and database coverage. [1]

Award Suitability

The supplied profile identifies Mingxiong He as working in Omics Data Analysis and provides documented bibliometric indicators of 133 documents, 4,058 citations, and an h-index of 34. These details are relevant to an academic recognition profile associated with the Computational Biologists Awards, particularly where evaluation considers research activity, scholarly output, and documented research impact. [1]

Conclusion

Mingxiong He is presented in the supplied profile as a researcher associated with the Biogas Iinstitute of Ministry of Agriculture and Rural Affairs in China, with Omics Data Analysis identified as the subject area. The reported Scopus record contains 133 documents, 4,058 citations, and an h-index of 34. These indicators provide a quantitative overview of scholarly activity and citation accumulation. A fuller academic assessment would require review of individual publications, research methods, collaboration, datasets, and documented applications alongside the bibliometric record.

References

  1. Elsevier. (n.d.). Scopus author details: Mingxiong He, Author ID 18436995800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=18436995800
  2. ORCID. (n.d.). ORCID record: Mingxiong He, ORCID iD 0000-0002-9780-6865.
    https://orcid.org/0000-0002-9780-6865
  3. Journal article(2017. )  Acinetobacter larvae sp. nov., isolated from the larval gut of omphisa fuscidentalis.
    https://doi.org/10.1099/ijsem.0.001644
  4. Journal article(2017. ) Bio-ethanol production by Zymomonas mobilis using pretreated dairy manure as a carbon and nitrogen source.
    https://doi.org/10.1039/c6ra26288k
  5. Computational Biologists Awards. (2026. ) Computational Biologists Awards official website.
    https://computationalbiologists.com/

Pramod singh | Omics Data Analysis | Research Excellence Award

Research Excellence Award

Pramod singh
Affiliation Netaji Subhas University
Country India
Google Scholar zxaambsAAAAJ&hl
Documents 53
Citations 355
h-index 11
Subject Area Omics Data Analysis
Event Computational Biologists Awards

PRAMOD SINGH

Netaji Subhas University, India

Pramod singh is an academic researcher associated with Netaji Subhas University whose scholarly activities focus on Omics Data Analysis and computational approaches for interpreting biological information. His publication record, citation profile, and continuing research contributions demonstrate sustained engagement with multidisciplinary investigations involving genomics, bioinformatics, and data-driven biological interpretation. The following article presents an encyclopedic overview of his academic profile, research interests, publication activity, and relevance for recognition through the Computational Biologists Awards.[1]

Abstract

Pramod singh has developed a scholarly profile centered on Omics Data Analysis through interdisciplinary computational research integrating biological datasets with analytical methodologies. His publications contribute to improved interpretation of genomic information, biological variability, and computational modeling that supports modern life science investigations. Citation indicators and documented research productivity reflect continued academic engagement within bioinformatics and systems biology. His work emphasizes reproducible scientific analysis, collaborative investigation, and evidence-based interpretation of complex biological information, providing valuable support for researchers seeking meaningful biological insights from rapidly expanding omics resources while encouraging future computational innovations.[1]

Keywords

Omics Data Analysis, Bioinformatics, Computational Biology, Genomics, Systems Biology, Biological Data Mining, Data Integration, Scientific Computing.

Introduction

Computational biology increasingly depends upon advanced analytical methods capable of interpreting extensive biological datasets produced through modern experimental technologies. Researchers working within omics sciences contribute by combining computational techniques with biological knowledge to reveal meaningful relationships among genes, proteins, and molecular pathways. Pramod singh has participated in this evolving research landscape through studies supporting data interpretation and biological discovery while maintaining an active academic publication record.[2]

Research Profile

The research profile demonstrates sustained scholarly productivity, including fifty-three documented publications, three hundred thirty-five citations, and an h-index of eleven according to the supplied academic metrics. Affiliated with Netaji Subhas University, the researcher investigates computational methodologies applicable to omics data interpretation and contributes to multidisciplinary biological research through quantitative analysis, scientific collaboration, and publication in recognized scholarly literature.[1]

Research Contributions

Research contributions emphasize computational strategies for analyzing complex biological information generated from modern omics technologies. Such work commonly supports improved biological interpretation through statistical modeling, computational workflows, and integrated data analysis. These contributions encourage reproducibility, facilitate interdisciplinary collaboration, and strengthen scientific understanding by transforming large-scale biological observations into interpretable knowledge supporting future experimental and computational investigations.[2]

Publications

The documented publication portfolio reflects continued scholarly engagement across computational biology and omics research themes. Published studies contribute to scientific communication by presenting analytical findings, computational methodologies, and biological interpretations relevant to contemporary bioinformatics. The publication record, together with citation performance, indicates ongoing visibility within the research community and demonstrates active participation in knowledge dissemination.[1]

Research Impact

Research impact is reflected through measurable citation performance and the broader applicability of computational approaches for biological data analysis. Published findings support subsequent investigations by providing analytical perspectives and methodological references that may assist researchers working across genomics, molecular biology, and bioinformatics. Such influence contributes to cumulative scientific progress while encouraging continued interdisciplinary research development.[2]

Award Suitability

Based on the documented academic profile, publication productivity, citation metrics, and specialization in Omics Data Analysis,Pramod singh demonstrates characteristics commonly considered during scholarly recognition processes. His sustained research activity and measurable academic contributions align with the objectives of the Computational Biologists Awards, which acknowledge researchers advancing computational methods for biological discovery through high-quality scientific investigation and interdisciplinary collaboration.[1]

Conclusion

Pramod singh represents an active researcher contributing to computational biology through Omics Data Analysis and scholarly publication. His documented academic indicators, interdisciplinary research interests, and continuing engagement with computational biological sciences illustrate a consistent commitment to scientific advancement. Collectively, these characteristics provide a strong academic foundation supporting recognition within professional research award programs dedicated to computational biology excellence.[2]

External Links

References

  1. Google Scholar Profile of Pramod singh.
    https://scholar.google.com/citations?user=zxaambsAAAAJ&hl=en
  2. Biochemistry Research International.(2026.) Characterization of Seed Storage Proteins from Chickpea Using 2D Electrophoresis Coupled with Mass Spectrometry.
    https://doi.org/10.1155/2016/1049462
  3. Computational Biologists Awards.(2026.) Official Award Website.
    https://computationalbiologists.com/

Prof. Arn Mignon | Quantitative Biology | Research Excellence Award

Prof. Arn Mignon | Quantitative Biology | Research Excellence Award

KU Leuven University | Belgium

Prof. Arn Mignon, Associate Professor at KU Leuven, is a distinguished researcher in advanced biomaterials and polymer science with strong interdisciplinary relevance to computational biology. Holding a PhD in Chemical Engineering, he has developed significant expertise in smart polymers, nanoparticle synthesis, and electrospinning-based additive manufacturing. Since establishing his Smart Polymeric Biomaterials research group, he has led innovative work on stimuli-responsive drug delivery systems targeting wound healing, tissue repair, and biomedical implants. With over 50 journal publications, 3 patents, and a strong citation record (h-index 28), his research integrates material design with biomedical applications, demonstrating impactful contributions aligned with the vision of the Computational Biologists Awards.

Citation Metrics (Scopus)

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2,769

Documents
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h-index
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Ann Aerts | Epigenomic Data Integration | Research Excellence Award

Dr. Ann Aerts | Epigenomic Data Integration | Research Excellence Award

Novartis Foundation | Switzerland

Dr. Ann Aerts is a global health leader and physician who serves as Head of the Novartis Foundation, where she drives initiatives to transform urban population health through data, digital technology, and AI. With a medical degree and a Master’s in Public Health from the University of Leuven, along with training from the Institute of Tropical Medicine Antwerp, she combines clinical expertise with innovation. Ann is known for advancing multisector partnerships and scalable digital health solutions to reduce global health disparities. She also chairs the Broadband Commission Working Group on Digital and AI in Health and serves on several international boards, contributing to more resilient and preventive healthcare systems worldwide.

Citation Metrics (Scopus)

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1,239
Documents
49
h-index
16

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