philippkhaitovich

Philipp Khaitovich

Philipp Khaitovich, born in Moscow, Russia in 1973.

Philipp completed undergraduate studies in molecular biology at Moscow State University in 1995 and PhD in biochemistry at the University of Illinois at Chicago in 1999.

From 2000 till 2006 Philipp worked as a postdoctoral researcher at the Max Planck Institute for Evolutionary Anthropology at the department of Evolutionary Genetics headed by Prof. Svante Pääbo.

In September 2006, Philipp took a faculty position at the Institute for Computational Biology jointly established by the Chinese Academy of Sciences and the Max Planck Society in Shanghai China. In 2012 Philipp was promoted to an institute director position.

From 2012, Philipp is a fellow member of Max Planck Society of Germany, as well as adjunct Professor at ShanghaiTech University in Shanghai, China.

Philipp joined Skoltech as a Full Professor in April 2014.

The research conducted in Philipp’s laboratory is built on a combination of the following resources and instruments:

  • Collection of unique human and non-human samples.
  • Use of novel high-throughput data generation methods, including high-throughput sequencing and high precision mass spectrometry to generate comprehensive datasets covering gene structure (splicing) and activity (expression), as well as cellular and organismal physiology estimated using concentrations of thousands of biochemical markers: metabolites and lipids.
  • Use of novel analytical tools and algorithms to analyze data and intergrade heterogeneous data types.
  • Use of classical laboratory approaches, including microscopy and immunohistochemistry, as well as cell culture and organism-level experiments, to verified specific results obtained by the analysis of large datasets.

We use various combinations of these resources and instruments to get insights into complex biological problems, with the main focus on:

  • Evolution of cognitive abilities unique to humans or particularly advances in humans.
  • Metabolic and structural organization of the human brain, its evolution and variability across human populations.
  • Molecular features of natural and artificial selections in humans and domesticated species.
  • the Friendship medal (China)
Svetlana Goryunova
Senior Research Scientist
Nikolay Anikanov
Technician
alinachernova
Alina Chernova
PhD student
Olga Efimova
Technician
annaegorova
Anna Egorova
MSc student
denisgoruynov
Denis Goryunov
Research Scientist
songguo
Song Guo
PhD student
ekaterinakhrameeva
Ekaterina Khrameeva
Research Scientist
iliakurochkin
Ilia Kurochkin
PhD student
alekseimikhalchenko
Aleksei Mikhalchenko
PhD student
vitastepanova
Vita Stepanova
PhD student
annatkachev
Anna Tkachev
PhD student
alexandertyshkovskii
Alexander Tyshkovskiy
PhD student
annavanyushkina
Anna Vanyushkina
Research Scientist
pavelmazin
Pavel Mazin
Junior Research Scientist
ekaterinayushina
Ekaterina Yushina
Research Intern
dmitryzubkov
Dmitry Zubkov
PhD student
  • Advanced Bioinformatics Lab
The course will introduce students to the hands-on practical analysis of novel biological “omics” data with a specific focus on the state-of-the-art analysis of the genome, epigenome, and transcriptome. The course will integrate various types of omics data generated by new generation sequencing technologies and will include the following parts: genome assembly, genotyping and GWAS analyses in the genome section; histone modifications, DNA methylation and 3D chromatin organization in the epigenetics section; transcriptome assembly, splicing analysis, RNA editing, differential transcription, non-coding RNA analysis and functional characterization in transcriptome section. In addition, the course will integrate various types of omics data, including data generated by mass spectrometry-based approaches, as well as axillary data new generation sequencing technologies.The course will include practical data analysis work conducted by the student in front of a computer, but also introductory lectures into principles of data analysis and basic elements of statistical analysis of large-scale biological data.At the end of the course, students would be expected to accomplish an independent data analysis project on a model dataset including several heterogeneous types of biological “omics” data.

ФИО: Хайтович Филипп Ефимович

Занимаемая должность (должности): Профессор

Преподаваемые дисциплины: –

Ученая степень: Ph.D., Университет Иллинойса в Чикаго, США, 1999

Ученое звание (при наличии): нет

Наименование направления подготовки и/или специальности: Биохимия

Данные о повышении квалификации и/или профессиональной переподготовке (при наличии): нет

Общий стаж работы: 15 лет

Стаж работы по специальности: 15 лет