Lilia Alberghina

About Lilia Alberghina

Lilia Alberghina, With an exceptional h-index of 60 and a recent h-index of 28 (since 2020), a distinguished researcher at Università degli Studi di Milano-Bicocca, specializes in the field of Systems Biology.

His recent articles reflect a diverse array of research interests and contributions to the field:

Fusion–fission–mitophagy cycling and metabolic reprogramming coordinate nerve growth factor (NGF)‐dependent neuronal differentiation

The Warburg effect explained: integration of enhanced glycolysis with heterogeneous mitochondria to promote cancer cell proliferation

Coupling constrained-based flux sampling and clustering to tackle cancer metabolic heterogeneity

A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations

CDK12 promotes tumorigenesis but induces vulnerability to therapies inhibiting folate one-carbon metabolism in breast cancer

INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

Transcriptomics and metabolomics integration reveals redox-dependent metabolic rewiring in breast cancer cells

Lilia Alberghina Information

University

Position

Emeritus Professor of Biochemistry

Citations(all)

13839

Citations(since 2020)

3068

Cited By

11917

hIndex(all)

60

hIndex(since 2020)

28

i10Index(all)

224

i10Index(since 2020)

83

Email

University Profile Page

Google Scholar

Lilia Alberghina Skills & Research Interests

Systems Biology

Top articles of Lilia Alberghina

Fusion–fission–mitophagy cycling and metabolic reprogramming coordinate nerve growth factor (NGF)‐dependent neuronal differentiation

The FEBS Journal

2024/2/16

The Warburg effect explained: integration of enhanced glycolysis with heterogeneous mitochondria to promote cancer cell proliferation

2023/10/31

Lilia Alberghina
Lilia Alberghina

H-Index: 29

Coupling constrained-based flux sampling and clustering to tackle cancer metabolic heterogeneity

2023/3/1

A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations

bioRxiv

2023

CDK12 promotes tumorigenesis but induces vulnerability to therapies inhibiting folate one-carbon metabolism in breast cancer

Nature communications

2022/5/12

INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation

PLoS computational biology

2022/2/7

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

BMC medical informatics and decision making

2021/12

Transcriptomics and metabolomics integration reveals redox-dependent metabolic rewiring in breast cancer cells

Cancers

2021/10/9

Methotrexate inhibits SARS‐CoV‐2 virus replication “in vitro”

Journal of medical virology

2021/3

Disruption of redox homeostasis for combinatorial drug efficacy in K-Ras tumors as revealed by metabolic connectivity profiling

Cancer & metabolism

2020/12

ROS networks: designs, aging, Parkinson’s disease and precision therapies

NPJ systems biology and applications

2020/10/26

Use of Protein Distribution to Analyze Budding Yeast Population Structure and Cell Cycle Progression

2020/7/24

Lilia Alberghina
Lilia Alberghina

H-Index: 29

Systems metabolomics: From metabolomic snapshots to design principles

2020/6/1

Elena Sacco
Elena Sacco

H-Index: 10

Lilia Alberghina
Lilia Alberghina

H-Index: 29

Nicotinamide, nicotinamide riboside and nicotinic acid—emerging roles in replicative and chronological aging in yeast

2020/4/15

Ivan Orlandi
Ivan Orlandi

H-Index: 12

Lilia Alberghina
Lilia Alberghina

H-Index: 29

Fuzzy modeling and global optimization to predict novel therapeutic targets in cancer cells

Bioinformatics

2020/4/1

Neurons, glia, extracellular matrix and neurovascular unit: a systems biology approach to the complexity of synaptic plasticity in health and disease

2020/2/24

G. Appendix III

Dr. Thomas Bruhn, Science Officer at EMRC, who coordinated and oversaw the editing of the report.

2020

Single-cell digital twins for cancer preclinical investigation

Metabolic Flux Analysis in Eukaryotic Cells: Methods and Protocols

2020

From computational genomics to systems metabolomics for precision cancer medicine and drug discovery

Pharmacological research

2020

Lilia Alberghina
Lilia Alberghina

H-Index: 29

Gennaro Piccialli
Gennaro Piccialli

H-Index: 18

See List of Professors in Lilia Alberghina University(Università degli Studi di Milano-Bicocca)