Updated docs to commit 713abfcc46ab174d4f6da83316af370c1b514636.

seminar/index.html

@@ -124,17 +124,16 @@ <h4>How to apply as a speaker</h4>
         <p>The seminar is a great opportunity to present your recent work to a large international audience.
             If you want to apply as a speaker, please use the contact in the registration confirmation email.</p>
         <h4>Next seminar</h4>
-        <h6> Title: Bridging AI and Single-cell Genomics: Towards AI-driven Discoveries </h6> 6 March 2024 5:30 p.m. - 6:30 p.m. Central European Time
-        <p>Speaker: <strong><a href="https://people.epfl.ch/maria.brbic">Maria Brbić</a></strong>, EPFL, Lausanne</p>
+        <h6> Title: Sequence basis of transcription Initiation in human genome </h6> 3 April 2024 5:30 p.m. - 6:30 p.m. Central European Time
+        <p>Speaker: <strong><a href="http://zhoulab.io/">Kseniia Dudnyk, Jian Zhou lab</a></strong>, UT Southwestern Medical Center</p>
         <strong>Abstract:</strong>
         <p align="justify">
-            The advancements in single-cell technologies have enabled the generation of large-scale datasets across different tissues, conditions and species, offering opportunities for defining new cell states and uncovering underlying cellular processes. In this talk, I will present machine learning methods that have the ability to bridge heterogeneity of single cell datasets by enabling analysis, annotation transfer and discovery of novel cell types across different tissues, conditions and species. I will discuss the findings and impact these methods have for annotating comprehensive single-cell atlas datasets, as well as their role in moving beyond conventional machine learning paradigms to enable new scientific discoveries.
+            Transcription initiation is an essential process for ensuring proper function of any gene, however, we still lack a unified understanding of sequence patterns and rules that explains most transcription initiation sites in human genome. By explaining transcription initiation at basepair resolution from sequence with a deep learning-inspired explainable modeling approach, we show that simple rules can explain the vast majority of human promoters. We identified key sequence patterns that contribute to human promoter function, each activating transcription with a distinct position-specific effect curve that likely reflects its mechanism of promoting transcription initiation. Most of these position-specific effects have not been previously characterized, and we verified them using experimental perturbations of transcription factors and sequences. We revealed the sequence basis of bidirectional transcription at promoters and links between promoter selectivity and gene expression variation across cell types. Additionally, by analyzing 241 mammalian genomes and mouse transcription initiation site data, we showed that the sequence determinants are conserved across mammalian species. Taken together, we provide a unified model of the sequence basis of transcription initiation at the basepair level that is broadly applicable across mammalian species, and shed new light on basic questions related to promoter sequence and function.
         </p>
 
         <h4>Upcoming speakers</h4>
         <div class="container-fluid">
             <ul class="list-unstyled">
-                <li>3 April 2024 - <a href="http://zhoulab.io/">Kseniia Dudnyk, Jian Zhou lab</a>, UT Southwestern Medical Center</li>
                 <li>8 May 2024 - <a href="">TBD</a>, </li>
                 <li>5 June 2024 - <a href="">TBD</a>, </li>
                 <li>3 July 2024 - <a href="https://www.tewheylab.org/">Sagar Gosai, Ryan Tewhey lab</a>, The Jackson laboratory</li>
@@ -144,6 +143,7 @@ <h4>Upcoming speakers</h4>
         <h4>Previous speakers</h4>
         <div class="container-fluid">
         <ul class="list-unstyled">
+            <li>6 March 2024 - <a href="https://people.epfl.ch/maria.brbic">Maria Brbić</a>, EPFL, Lausanne</li>
             <li>7 February 2024 - <a href="http://erictnguyen.com/">Eric Nguyen, Christopher Ré lab</a>, Stanford University</li>
             <li>10 January 2024 - <a href="http://koolab.cshl.edu/">Peter Koo</a>, Cold Spring Harbor Laboratory</li>
             <li>6 December 2023 - <a href="https://imk1.github.io/">Irene Kaplow</a>, Duke University</li>