Xuecong Fu's research while affiliated with Carnegie Mellon University and other places
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Publications (11)
Motivation:
Cells contain dozens of major organelles and thousands of other structures, many of which vary extensively in their number, size, shape and spatial distribution. This complexity and variation dramatically complicates the use of both traditional and deep learning methods to build accurate models of cell organization. Most cellular organ...
Motivation:
Cancer develops through a process of clonal evolution in which an initially healthy cell gives rise to progeny gradually differentiating through the accumulation of genetic and epigenetic mutations. These mutations can take various forms, including single-nucleotide variants (SNVs), copy number alterations (CNAs) or structural variatio...
Motivation:
Identifying cell types and their abundances and how these evolve during tumor progression is critical to understanding the mechanisms of metastasis and identifying predictors of metastatic potential that can guide the development of new diagnostics or therapeutics. Single-cell RNA sequencing (scRNA-seq) has been especially promising in...
Identifying how cell types and their abundances evolve during tumor progression is critical to understanding the mechanisms and identifying predictors of metastasis. Single-cell RNA sequencing (scRNA-seq) has been especially promising in resolving heterogeneity of expression programs at the single cell level but is not always available, for example...
Motivation
Cells contain dozens of major organelles and thousands of other structures, many of which vary extensively in their number, size, shape and spatial distribution. This complexity and variation dramatically complicates the use of both traditional and deep learning methods to build accurate models of cell organization. Most cellular organel...
Phylogenetic inference has become a crucial tool for interpreting cancer genomic data, but continuing advances in our understanding of somatic mutability in cancer, genomic technologies for profiling it, and the scale of data available have created a persistent need for new algorithms able to deal with these challenges. One particular need has been...
Aneuploidy and whole genome duplication (WGD) events are common features of cancers associated with poor outcomes, but the ways they influence trajectories of clonal evolution are poorly understood. Phylogenetic methods for reconstructing clonal evolution from genomic data have proven a powerful tool for understanding how clonal evolution occurs in...
Motivation:
Computational reconstruction of clonal evolution in cancers has become a crucial tool for understanding how tumors initiate and progress and how this process varies across patients. The field still struggles, however, with special challenges of applying phylogenetic methods to cancers, such as the prevalence and importance of copy numb...
Motivation:
Cancer develops and progresses through a clonal evolutionary process. Understanding progression to metastasis is of particular clinical importance, but is not easily analyzed by recent methods because it generally requires studying samples gathered years apart, for which modern single-cell sequencing is rarely an option. Revealing the...
Computational reconstruction of clonal evolution in cancers has become a crucial tool for understanding how tumors initiate and progress and how this process varies across patients. The field still struggles, however, with special challenges of applying phylogenetic methods to cancers, such as the prevalence and importance of copy number alteration...
Citations
... These meshes are exported as 3D models in a generic Wavefront OBJ format (Fig. 1D, SI Section 1.2) which is compatible with other modeling and simulation programs including Blender and 3Dsmax. Biologists frequently resort to manual segmentation due to lack of sufficient training data for deep learning methods, high cost of generating ground-truth data (Sun et al., 2022) and need for retraining the algorithms for different morphologies, resolution, image quality, or acquisition techniques (Meijering, 2020;Pelt, 2020). In such cases the modularized CellWalker pipeline allows the users to use such manual or hand-painted image segmentations directly for 2D/3D morphological characterization of segmented objects. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/272441171771401-1441966445321_Q64/Robert-Murphy-6.jpg)
... Furthermore, single-cell data, particularly single-cell DNA-seq (scDNA-seq), remains costly to gather and thus all large tumor data resources are still based on bulk sequence. Some methods have been proposed to combine bulk and single-cell sequence (Lei et al., 2020;Malikic et al., 2019) or other heterogeneous data combinations (Fu et al., 2021;Lei et al., 2021), but major sequencing efforts to date have i125 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/749472946597889-1555699683328_Q64/Haoyun-Lei-2.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/285785971544065-1445148093920_Q64/Yifeng-Tao.jpg)
... Furthermore, single-cell data, particularly single-cell DNA-seq (scDNA-seq), remains costly to gather and thus all large tumor data resources are still based on bulk sequence. Some methods have been proposed to combine bulk and single-cell sequence (Lei et al., 2020;Malikic et al., 2019) or other heterogeneous data combinations (Fu et al., 2021;Lei et al., 2021), but major sequencing efforts to date have i125 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/272430040088587-1441963791450_Q64/Alejandro-Schaffer.jpg)
... Bioinformatics, 38, 2022, i386-i394 https://doi.org/10.1093/bioinformatics/btac262 ISCB/ISMB 2022 gradient descent implemented through a neural network; and RAD (Tao et al., 2020b), which solve s the formulation of NND using a hybrid optimizer with improved accuracy and speed. ...
... This is supported by a previous study of younger breast cancer patients in which WGD was shown to occur but was not required for tumorigenesis [9]. Furthermore, it is consistent with a study of Lei et al. describing WGD as neither necessary for tumorigenesis nor necessarily a one-time event in cancer evolution [70]. ...
