Xin Lai @laixinking

A Systems Biologist with passion for research, photograph, and cook. sites.google.com/view/lai-lab Finland Joined December 2009

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ISCB News @iscb

a month ago

🚨Paper submissions to iscbAI are due tomorrow, Monday, June 1! 📥 Submit here: iscb-cn.org.cn/web/72/list.ht…

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Xin Lai @laixinking

2 months ago

New research in @CMLS_Journal provides the first systematic look at SOX10-mediated miRNA regulation in Uveal Melanoma (UM). 🔗 Read the full study here: rdcu.be/fjbeA #UvealMelanoma #CancerResearch #SystemsBiology #miRNA #Bioinformatics #Oncology #PrecisionMedicine

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Xin Lai @laixinking

4 months ago

@acagamic Thanks so much for sharing your insights and experience.

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Xin Lai @laixinking

6 months ago

The Biorxiv preprint is available at doi.org/10.64898/2026.…

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We develop #RingNet to visualize #multi-modal data in #networks. It is powerful to visualize your #cohort and #single-cell #omics data. All you need are the csv files for your data and networks, and RingNet can support svg, pdf output. Try it out at fip-128-214-252-149.kaj.poutavm.fi/cmt_figures/

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Xin Lai @laixinking

7 months ago

The latest research from Guo's lab at @theNCI shows that one hotspot mutation in #DICER1's RNase IIIb can lead to loss and gain of function 5p-miRNA and the gain of function of 3p-miRNA. rdcu.be/eUxiq

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Xin Lai @laixinking

9 months ago

See our new preprint, where we used a network biology method to identify novel therapeutic targets for uveal #melanoma. #networkmedicine #bioinformatics #cancer

bioRxiv Cancer Bio @biorxiv_cancer

9 months ago

A computational SOX10 network-based selection strategy to identify new drug targets in uveal melanoma biorxiv.org/content/10.110… #biorxiv_cancer

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Xin Lai @laixinking

9 months ago

Seedless binding in #miRNAs can also lead to gene repression as shown with miR-155 and miR-124, though this unconventional binding accounts ~1% of miRNA binding. See Bartel lab's new paper for details. Functional microRNA targeting without seed pairing academic.oup.com/nar/article/53…

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Xin Lai @laixinking

9 months ago

New preprint on IDH-mutant #astrocytomas: We analyzed rare patient samples showing grade 2-3→4 progression post-therapy. Key findings: #ncRNAs drive astrocyte dedifferentiation; tumor suppressor #miRNA let-7b-3p shows recurrent deletions; #lncRNA NEAT1 regulates ECM organization

bioRxiv Cancer Bio @biorxiv_cancer

9 months ago

Integrative multi-modal analysis reveals the contribution of noncoding RNAs to post-treatment progression of IDH-mutant astrocytomas biorxiv.org/content/10.110… #biorxiv_cancer

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Xin Lai @laixinking

10 months ago

Our commitment to open science means the HallmarkGraph data and code are publicly available on #GitHub and #Zenodo. #OpenScience #FAIRdata #Research #GitHub #DataSharing github.com/laixn/Hallmark… doi.org/10.5281/zenodo…

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Xin Lai @laixinking

10 months ago

We built HallmarkGraph to be transparent. By integrating gene-level features with cancer hallmarks, we can now provide clear explanations for our model's predictions. #InterpretableAI #ComputationalOncology #MedicalAI

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Xin Lai @laixinking

10 months ago

New publication at #Bioinformatics of @OxfordJournals. HallmarkGraph: a cancer hallmark informed graph neural network for classifying hierarchical tumor subtypes #CancerResearch #MachineLearning #AIinMedicine #PrecisionOncology academic.oup.com/bioinformatics…

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Xin Lai @laixinking

11 months ago

The forum's emphasis on translating academic research into practical applications through industry partnerships reflects the urgent need for scalable, data-driven healthcare solutions that can be deployed globally to improve patient outcomes and population health management.

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Xin Lai @laixinking

11 months ago

The second day's session on the digitization of health benefited greatly from the participation of high-level government officials and Chinese and Finnish companies, including @avaintec , @AtostekOy , SOENIA®, @NADMED_Ltd, 神州医疗.

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Xin Lai @laixinking

11 months ago

The 2nd China-Germany-Finland Life Sciences Forum, held at Tampere University, has successfully concluded. The forum brought together 60 researchers from five countries. The forum focused on AI in biomedical research and health data science innovation. tuni.fi/en/news/intern…