Ying Ma
@yingma0107
Followers
756
Following
902
Media
0
Statuses
134
Statistical genetics and genomics. Assistant Professor at Brown Biostats @BrownBiostats and Brown CCMB @BrownCCMB
Providence, RI
Joined July 2019
Don't wanna be here?
Send us removal request.
Explore trending content on Musk Viewer
#FreeBilly
• 678936 Tweets
Ronaldo
• 320371 Tweets
BABY I'M A ROCKSTAR
• 199479 Tweets
Portugal
• 197553 Tweets
Arda
• 193624 Tweets
THE UNTOLD SHORT FILM
• 116217 Tweets
Portekiz
• 105662 Tweets
Yunus
• 96792 Tweets
Turkey
• 91820 Tweets
Montella
• 89663 Tweets
#TURvPOR
• 73646 Tweets
Samet
• 65461 Tweets
Kerem
• 64853 Tweets
Where is Billy
• 59682 Tweets
Yusuf
• 53248 Tweets
Japão
• 52326 Tweets
Altay
• 51665 Tweets
Mert
• 51528 Tweets
Kenan
• 49715 Tweets
Semih
• 46660 Tweets
Lando
• 44178 Tweets
Turquía
• 43070 Tweets
Hakan
• 33174 Tweets
Barış Alper
• 29543 Tweets
Hamit
• 29304 Tweets
Leao
• 28513 Tweets
ブラジル
• 28166 Tweets
Ferdi
• 26463 Tweets
Bruno Fernandes
• 26261 Tweets
İsmail
• 24224 Tweets
Zeki
• 23184 Tweets
İstifa
• 21670 Tweets
Hakem
• 21369 Tweets
#التقويم_الدراسي
• 20547 Tweets
#MilliTakım
• 18986 Tweets
Bernardo Silva
• 18980 Tweets
Gürcistan
• 18936 Tweets
Abdülkerim
• 17788 Tweets
Cancelo
• 17541 Tweets
Orkun
• 16377 Tweets
Çekya
• 14494 Tweets
Stolas
• 14289 Tweets
Uğurcan
• 12931 Tweets
Mehmet Büyükekşi
• 12221 Tweets
Pinned Tweet
🎉 Thrilled to share our latest method, IRIS, now published in
@naturemethods
！IRIS is a robust statistical and computational method designed to decode the spatial organization of tissues. It efficiently detects biologically interpretable spatial domains across multi-samples.
Integrative and reference-informed tissue segmentation (IRIS) from Ying Ma & Xiang Zhou harnesses scRNA-seq data for the accurate identification of spatial domains in spatially resolved transcriptomics. IRIS is uniquely suited for analyzing large datasets.
0
23
72
7
29
146
I am honored to receive the pilot award and grateful for the opportunity to advance our research!
Congratulations to Ying Ma, Ph.D., Assistant Professor of Biostatistics, for receiving the American Cancer Society Institutional Research Grant Pilot award!
@Brown_SPH
| 🔗
0
4
32
16
9
178
Check out our recent work CARD, a computational fast and memory efficient statistical tool to (1) perform spatially informed cell type deconvolution with or without single cell RNAseq (scRNA-seq) reference
Spatially informed cell-type deconvolution for spatial transcriptomics
0
21
67
4
35
153
🎉 Thrilled to announce my new role at
@BrownBiostats
and
@BrownCCMB
! 🌟 It's been an incredible first week, meeting wonderful, dedicated, and brilliant people driving impactful work in the community. 🙌 Excited for the boundless opportunities ahead at Brown. 📚
We are pleased to welcome our new Assistant Professor of Biostatistics Ying Ma, PhD to
@BrownUniversity
@Brown_SPH
Department of Biostatistics. Welcome Ying! (
@yingma0107
)
0
3
28
19
12
122
Big Congratulations to
@xiangzhoulab
and
@LabWelch
and all the outstanding scientists!
The
@UMich
’s Biosciences Initiative has selected five accomplished scientists as the 2024 recipients of the Mid-career Biosciences Faculty Achievement Recognition Award.
2
13
53
0
0
13
Our work on Exposure Polygenic Risk Scores (ExPRS) is now online
@AJHGNews
. We share all ExPRS constructs and results via an online interactive repository here:
1
3
11
Check our group’s new paper discussing the zero inflation problems in spatial transcriptomics！A comprehensive analysis on 20 spatial transcriptomics data sets across 11 different technologies performed by Peiyao Zhao!
Zhao,
@xzlab_org
& co present a study of excessive zeroes in spatial transcriptomics. In 20 datasets using 11 different technologies, genes can be modeled with Poisson or negative binomial, showing that accounting for zero inflation is not necessary
0
8
23
0
3
9
A Bayesian polygenic risk score (PRS) method that leverages shared genetic effects across ancestries to increase PRS portability
0
0
5
Congrats on the great work published in
@GenomeBiology
！
Our new method, TDEseq has been published on
@GenomeBiology
. It primarily builds upon a linear additive mixed model framework to facilitate the detection of four potential temporal gene expression patterns, i.e., growth, recession, peak, or trough.
0
2
7
0
0
5
🎉👏Big congratulations to Dr.
@BhramarBioStat
on this well-deserved achievement! 🌟 We are truly blessed to have such an exceptional and inspiring leader in our Umich Biostats department. 🌟 Thank you for your continuous support and invaluable suggestions!
Cannot believe this happened. A surreal feeling.
I had a planned thread and a composed reaction but cannot remember a word of it.
Tears of joy in my eyes this evening to receive the highest professorship of this magnificent University...Thanks
@UMich
@umichsph
@UMRogelCancer
87
36
890
0
0
6
Congragts, Maria! Fantastic work!
Our 🪐SATURN method is now out in
@naturemethods
!
SATURN paves the way for universal cell embeddings, enabling integration of datasets across different species 🐒🐁🧍🐟🐸 Using protein language models, we encode biological meaning of genes in scRNA-seq datasets.
2
22
120
1
0
4
Congrats! 🎉🎊🍾
Excited to share that
@PCORI
has awarded funding for our proposed work developing Bayesian machine learning methods for causal inference!
Thanks to Roee Gutman (co-PI) & others at
@Brown_SPH
@Brown_Epi
@BrownUResearch
@BrownMedicine
@BrownUniversity
2
7
89
1
0
3
Check our new manuscript "ExPRSweb - An Online Repository with Polygenic Risk Scores for Common Health-related Exposures" () as well as our comprehensive interactive online repository of exposure PRS ().
0
0
4
Very nice work！
@_JiEun_Park_
Excited to share this work, collab with
@mikelove
et al!!
Diffsig can test the association btwn mutational signatures and “risk factors” which can be any variables of interest – continuous or categorical – and multiple risk factors can be tested at once:
3
26
99
1
0
2
Amazing work！
📣📣 Latest paper from the lab just out
@Nature
! An atlas of genetic scores to predict multi-omic traits
A new community resource to genetically impute multi-omics data at population-scale.
Check out OmicsPred portal
12
173
480
1
0
2
@XiuweiZhang
@ayirpelle
@naturemethods
Thank you for your kind words! Looking forward to connecting with you in future conferences!
0
0
3
Congratulations!🎉🎊🍾🎈
Our single-cell RNA-seq and ATAC-seq read simulator scReadSim is now online at
@NatureComms
scReadSim mimics real data at read-sequence and read-count levels, and it provides ground truths: UMI counts for RNA-seq and open chromatin regions for ATAC. 1/
7
50
259
1
0
2
0
0
2
@_JiEun_Park_
@shang_lulu
@WancenM
@FennecPaaaw
It was so happy to meet and chat with you all！Hope we can meet again in future conferences！
0
0
3
@Iqbalhu76038412
Thank you for your interest in my research! We are always open to working with motivated and talented students. However, the PhD admissions process in our department is managed though the Admission Committee. For more information, please see
1
0
1
(2) impute cell type compositions and gene expression levels, thus enabling the construction of a refined spatial tissue map.
0
0
1
0
0
1
@cgao90
Congratulations！So happy for you！
Iterative single-cell multi-omic integration using online learning
2
41
136
0
0
2
@KarthikeyaniC
Thank you, Karthikeyani! Also big congrats on your new position! Looking forward to potential collaborations!
0
0
1
0
0
1
0
0
1
0
0
1
2. We benchmarked IRIS against diverse methods and demonstrated its advantages through in-depth analysis of six SRT datasets from different technologies including 10x Visium, ST, Slide-seq, Vizgen MERFISH, Stereo-seq, and 10x Xenium across various tissues.
0
1
1
Congratulations on the great work! 🎉🎉🎉
Excited to share our paper in
@NatureBiotech
: Linger, a computational method for gene regulatory network inference from single cell multiome (RNA+ATAC) data.
17
84
340
1
0
1
1
0
1