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10 months ago
Rakesh Netha Vadnala,
Rakesh Netha Vadnala
Institution: 1The Institute of Mathematical Sciences,
Email: rakeshnetha@imsc.res.in
Sridhar Hannenhalli,
Sridhar Hannenhalli
Institution: National Cancer Institute, National Institutes of Health,
Email: rakeshnetha@imsc.res.in
Leelavati Narlikar,
Leelavati Narlikar
Institution: Department of Data Science, Indian Institute of Science Education and Research,
Email: rakeshnetha@imsc.res.in
Rahul Siddharthan
Rahul Siddharthan
Institution: The Institute of Mathematical Sciences,
Email: rakeshnetha@imsc.res.in
Transcription factors (TFs) and their binding sites have evolved to interact cooperatively or competitively with each other. Here we examine in detail, across multiple cell lines, such cooperation or competition among TFs both in sequential and spatial proximity (using chromatin conformation capture...
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Transcription factors (TFs) and their binding sites have evolved to interact cooperatively or competitively with each other. Here we examine in detail, across multiple cell lines, such cooperation or competition among TFs both in sequential and spatial proximity (using chromatin conformation capture assays) on one hand, and based on both in vivo binding as well as TF binding motifs on the other. We ascertain significantly co-occurring (“attractive”) or avoiding (“repulsive”) TF pairs using robust randomized models
that retain the essential characteristics of the experimental data. Across human cell lines TFs organize into two groups, with intra-group attraction and inter-group repulsion. This is true for both sequential and spatial proximity, as well as for both in vivo binding and motifs. Attractive TF pairs exhibit significantly more physical interactions suggesting an underlying mechanism. The two TF groups differ significantly in their genomic and network properties, as well in their function—while one group regulates housekeeping
function, the other potentially regulates lineage-specific functions, that are disrupted in cancer. We also show that weaker binding sites tend to occur in spatially interacting regions of the genome. Our results suggest a complex pattern of spatial cooperativity of TFs that has evolved along with the genome to support housekeeping and lineage-specific functions.
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1 year ago
Muhamed Amin
Muhamed Amin
Institution: Department of Sciences, University College Groningen, University of Groningen, Hoendiepskade
Email: m.a.a.amin@rug.nl
Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL) sources enabled the imaging
of the catalytic intermediates of the oxygen evolution reaction of Photosystem II. However, due to the
incoherent transition of the S-states, the resolved structures are a convolution from diff...
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Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL) sources enabled the imaging
of the catalytic intermediates of the oxygen evolution reaction of Photosystem II. However, due to the
incoherent transition of the S-states, the resolved structures are a convolution from different catalytic states.
Here, we train Decision Tree Classifier and K-mean clustering models on Mn compounds obtained from
the Cambridge Crystallographic Database to predict the S-state of the X-ray, XFEL, and CryoEm structures
by predicting the Mn's oxidation states in the oxygen evolving complex (OEC). The model agrees mostly
with the XFEL structures in the dark S1 state. However, significant discrepancies are observed for the
excited XFEL states (S2, S3, and S0) and the dark states of the X-ray and CryoEm structures. Furthermore,
there is a mismatch between the predicted S-states within the two monomers of the same dimer, mainly in
the excited states. The model suggests that improving the resolution is crucial to precisely resolve the
geometry of the illuminated S-states to overcome the noncoherent S-state transition. In addition, significant
radiation damage is observed in X-ray and CryoEM structures, particularly at the dangler Mn center (Mn4).
Our model represents a valuable tool for investigating the electronic structure of the catalytic metal cluster
of PSII to understand the water splitting mechanism.
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1 year ago
kavizio tr tr,
kavizio tr tr
Institution: Kaviapps
Email: tes@gmail.com
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1 year ago
